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Improving the safety andmobility of vulnerable road

users through ITSapplications [VRUITS] D2.3Implementation Scenarios

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Citation: MELENDEZ, A.B.G. ...et al., 2016. Improving the safety and mo-bility of vulnerable road users through ITS applications [VRUITS] D2.3 Imple-mentation Scenarios. VRUITS, 125pp.

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This project has received funding from the European Union’s Seventh

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demonstration under grant agreement no 321586

Grant agreement n° 321586

D2.3

Implementation Scenarios

Authors:

Alejandra Beatriz García Meléndez

Óscar Martín Pérez

CIDAUT Foundation

Andrew Morris

Graham Hancox

Loughborough University

Daniel Bell

FACTUM Chaloupka & Risser OHG

Dick Mans

ECORYS

Martijn van Noort

TNO

http://www.vruits.eu

© Copyright 2014 VTT

The copyright of this document is reserved on behalf of the VRUITS consortium by VTT.

The contents may not be disclosed without prior written consent of VTT

Deliverable information

Project no 321586

Project acronym vruits

Project title Improving the safety and mobility of vulnerable road users through ITS

applications

WP 2 VRU user needs, ITS prioritization and methodology

Task 2.5 Scenarios development

Deliverable D.2.3 Implementation scenarios

Status F: final

Version number 1.0

Lead Contractor CIDAUT

Dissemination level Public

Due date 30.06.2014

Date of preparation 29.10.2014

Project start and duration 1.4.2013–31.3.2016, 36 months

Project coordinator

Name Johan Scholliers

Organization VTT Technical Research Centre of Finland

email [email protected]

tel. +358 40 537 0204

fax +358 20 722 3365

Postal address:

P.O. Box 1300

FIN-33101 Tampere

Finland

Partners

http://www.vruits.eu/

III

Version history

Version Date Author Description

0.1 2014-14-01 Alejandra B. García Meléndez TOC

0.2 2014-22-04 Alejandra B. García Meléndez TOC updated based on feedback from

Ioannis Giannelos

0.3 2014-29-05 Alejandra B. García Meléndez Added Introduction, scope and objec-

tive of the deliverable, and first detail-

ing of Stakeholder consultation and

market assessment

0.4 2014-11-06 Daniel Bell First detailing of Mobility and comfort

data

0.5 2014-21-07 Andrew Morris

Graham Hancox

Safety trends

0.6 2014-24-07 Martijn van Noort First detailing of Road map for ITS

deployment

0.7 2014-25-07 Daniel Bell Update on Mobility and comfort data

0.8 2014-06-08 Daniel Bell Mobility and comfort forecast

0.9 2014-09-22 Dick Mans First detailing of Potential Business

models

0.11 2014-09-23 Óscar Martín, Alejandra Beat-

riz García Meléndez

Stakeholder consultation and market

assessment results

0.12 2014-10-09 Daniel Bell Update on mobility and comfort fore-

cast

0.13 2014-10-10 Óscar Martín, Alejandra Beat-

riz García Meléndez

Update on Stakeholder consultation

and market assessment results. Ap-

pendices added

D2.3


iv

Table of Contents

Table of Contents ..................................................................................................................................iv

List of abbreviations .............................................................................................................................vi

EXECUTIVE SUMMARY ........................................................................................................................vii

1. INTRODUCTION .............................................................................................................................. 1

1.1 VRUITS project ....................................................................................................................... 1 1.2 Scope and objective of the deliverable ................................................................................... 1

2. SAFETY TRENDS ............................................................................................................................ 3

2.1 Data needs ............................................................................................................................. 3 2.2 Compilation of accident data .................................................................................................. 3 2.3 Road safety trends and forecasts 2002 to 2030 .................................................................... 4

2.3.1 Results ....................................................................................................................... 4

3. MOBILITY AND COMFORT TRENDS ...........................................................................................10

3.1 Data needs ...........................................................................................................................10 3.2 Compilation of mobility and comfort data .............................................................................11

3.2.1 Mobility data .............................................................................................................13 3.2.2 Comfort data ............................................................................................................20

3.3 Mobility and comfort forecast................................................................................................24

3.3.1 Mobility forecast .......................................................................................................25 3.3.2 Comfort forecast ......................................................................................................29

4. MARKET ANALYSIS .....................................................................................................................32

4.1 Introduction ...........................................................................................................................32 4.2 Estimation on penetration rates: stakeholder consultation and market assessment ...........32

4.2.1 Procedure ................................................................................................................32 4.2.2 Results of the questionnaires ..................................................................................34 4.2.3 Second Interest Group Workshop ...........................................................................40 4.2.4 Combination of the questionnaire and IGW scenarios ............................................40 4.2.5 Translation of penetration rates to absolute numbers .............................................41

4.3 Potential business models ....................................................................................................43

4.3.1 What are business models ......................................................................................43 4.3.2 Business Model for Cooperative ITS .......................................................................44 4.3.3 Business Model In-vehicle ITS technology ..............................................................47 4.3.4 Business Model Public ITS ......................................................................................49 4.3.5 Business Model Cyclists Applications .....................................................................50

4.4 Road map for ITS deployment .............................................................................................52

D2.3


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5. DISCUSSION AND CONCLUSION ...............................................................................................57

REFERENCES .......................................................................................................................................58

APPENDICES

Appendix A. Questionnaires on penetration rates ..........................................................................60 Appendix B. Vehicle park Europe-28 ..............................................................................................88 Appendix C. Mobility data – overview of available mobility survey data of selected European

countries ...............................................................................................................................96 Appendix D. Comfort data – based on mobility and safety data ..................................................110

D2.3


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List of abbreviations

AEB Autonomous Emergency Braking

B2V Bicycle-to-car communication

BRM Cyclist digital bicycle rear-view mirror and rear obstacle detection

BSD Blind Spot Detection

CAL Crossing Adaptive Lighting

CBA Cost-benefit analysis

FOD Forward obstacle detection for cyclists

GWC Green Wave for Cyclists

IGW2 Second Interest Group Workshop

INS Intersection Safety

IPTS Intelligent pedestrian traffic signal

ISA Intelligent speed adaptation

ITS Intelligent Transport System

IVB Information on Vacancy on Bicycle racks

NAV Trip planning & navigation for VRU’s

NVW Night vision and warning

PDS+EBR Pedestrian Detection System + Emergency Braking

PPAA Public Administration

PTW Powered Two-Wheeler

PTW2V PTW oncoming vehicle information system

RTPI Real time information system for public transport

USS Urban sensing system

VBS VRU beacon system.

VRU Vulnerable road user. The categories considered in this deliverable are pedestrians, bicyclists and

PTWs

D2.3


vii

EXECUTIVE SUMMARY

ITS Applications have in recent years assisted in reducing the number of fatalities in Europe. Howev-

er, Vulnerable Road Users (VRUs) have not benefited as much as car users. The EU-sponsored

VRUITS project assesses the safety and mobility impacts of ITS applications for VRUs, assesses the

impacts of current and upcoming ITS applications on the safety and mobility of VRUs, identifies how

the usability and efficiency of ITS applications can be improved, and recommends which actions have

to be taken at a policy level to accelerate deployment of such ITS.

This report describes general scenarios for the years 2020 and 2030 providing developments focused

on road safety trends over time at the EU-level, as well as mobility and comfort trends of VRUs. Be-

sides a thorough market analysis has been performed on existing ITS as well as relevant trends and

market penetrations, for the applications, identified in VRUITS D2.1. Information has been collected

about the likelihood of applying these systems in future years, through questionnaires sent to public

administrations in charge of road infrastructure and manufacturers of ITS systems.

Safety trends

The CARE database has been analysed to predict the likely changes in road casualties during future

years. This prediction has been conducted making the assumption that there will be no effect of the

introduction of ITS systems.

The analysis of historical data from 2002 to 2012 shows that there is a significant decline in the num-

bers of accidents overall, with car occupant casualties showing a modest decrease. However, the de-

cline in accident numbers for the VRU´s is much less pronounced with bicycle and pedestrian casual-

ties remaining relatively constant.

Concerning the trends in fatalities and serious injuries for the same period, the decline for the VRU

groups are again much less pronounced than passenger cars. The trend for slightly injured casualties

is similar, although bicycle and pedestrian casualties appear to have increased slightly during the pe-

riod.

Based on this historical data a regression analysis has been made in order to predict the likely num-

bers of casualties for the year 2030.

Assuming that the current trends in road casualty numbers remain the same until 2030 car occupant

fatalities will decrease dramatically. However the predicted decrease for the VRU groups is not so

dramatic.

Mobility and comfort trends

Available data on the mobility and the comfort of vulnerable road users has been collected. In addition

potential trends in these regards have been identified based on current studies with focus on future

issues and needed measures and developments in different areas such as infrastructure, technology,

society, etc.

This chapter outlines definitions of mobility and comfort, and provides insight into the availability of

empiric date to measure these concepts. In addition a forecast and potential trends are discussed

based on found data and studies directly focussing on the issue of future VRU mobility.

Specifically mobility data detailing modal choice, trip lengths and duration of trips has been provided

for OECD countries. General trends in land use, spatial planning and policy objectives on both nation-

al and European levels hint at potential developments in the area of vulnerable road user mobility.

Overall general expectations are strongly focussing on the urban areas in Europe where technological

innovations in conjunction with spatial planning and improved public transport options help to develop

more car-free mobility profile for a broader range of road user groups. This in turn is expected to

change the modal split in the urban centres sustainable towards walking, cycling and also PTWs.

D2.3


viii

Concerning comfort the available studies have mainly focused on pedestrian comfort. For these the

assessed factors have included pollution, noise, weather protection, accessible activities, seating op-

portunities, illumination, toilet, pavement surface.

The development of specifically adapted infrastructure is expected to have the most influence on the

general usability and comfort for vulnerable road users in coming years. In general comfort of vulnera-

ble road users is expected to be strongly dependent on the space available especially for pedestrians

and bicyclists. In this regard there is still a high level of space shared between pedestrians and bicy-

clists and motorised traffic including public transport vehicles which in turn leads to higher demands

for safely and comfortably travelling in high density areas. Up until the year 2030 there is a trend to-

wards a more pedestrian friendly environment by providing more space dedicated to this road user

group.

Market analysis of ITS

The likelihood of applying the selected systems in 2020 and 2030 is analysed and the most appropri-

ate business model structures to increase the commercialization of these ITS are identified. Deploy-

ment issues of ITS for VRUs are discussed based on the analysis conducted.

Estimation of penetration rates: stakeholder consultation and market assessment

This subchapter aims at conducting a market analysis on the applications selected in the project. For

this purpose on the one hand information concerning the likelihood of applying these systems in 2020

and 2030 has been collected through questionnaires sent to PPAA in charge of road infrastructure and

manufacturers of ITS.

In addition, participants to the VRUITS Second Interest Group Workshop on 16.6.2014 in Helsinki,

were asked about the ease of deployment as well as time to market of these systems.

A description of the intended implementation rate for 2030 has been conducted merging the data

gathered through questionnaires, and through the IGW2. The following table shows the estimated

penetration rates, for the systems, which were selected at the Second Interest Group Workshop.

Table 1 Scenarios, obtained from combining questionnaire results with feedback from IGW2.

System Infrastructure penetration rate Users´ penetration rate

B2V 10% of bicycles; 40% of vehicles equipped with C-ITS

equipment supporting B2V functionality

BSD 44% of vehicles equipped

CAL 18% of major pedestrian crossings in

urban areas

GWC 1% of major intersections in urban

areas

10% of bicycles equipped

INS 5% of signalised intersections in urban

areas

40% of vehicles equipped with C-ITS equipment supporting

INS functionality

IPTS 32% of signalised intersections in ur-

ban areas

IVB 25% of bicycles equipped

PDS+EBR 36% of vehicles equipped

PTW2V 28% of PTWs equipped; 40% of vehicles equipped with C-

ITS equipment supporting PTW2V functionality

VBS 1% of major pedestrian crossings in

major cities

5% of pedestrians, 15% of cyclists;40% of PTWs equipped ;

40% of vehicles equipped (with C-ITS supporting equipment)

D2.3


ix

The obtained figures will be used for the quantitative impact assessment in WP3. In addition, the fig-

ures will be validated through a web questionnaire in November 2014.

Potential business models

This section aims to identify and suggest the most relevant and suitable business model structures to

increase the commercialization of the most promising and close-to-market ITS systems that are priori-

tized and assessed by VRUITS. Business models for four types ITS are discussed: Cooperative ITS,

In-vehicle ITS, Cyclists ITS and Public ITS.

Concerning cooperative ITS (INS, VBS, B2V, PTW2V), there is still a lack of knowledge on how coop-

erative ITS can be commercialized. For the development of a cooperative ITS, investments from mul-

tiple actors are needed. In some cases this involves vehicle manufacturers and infrastructure provid-

ers, in other cases it involves vehicle manufacturers and VRU device manufacturers. Smartphones are

also a good alternative to in-vehicle technology, given that they have a high market penetration which

enables a fast deployment of the technology. This is especially relevant for cooperative ITS, where a

critical mass of vehicles equipped with technology is necessary to create a viable business model.

However, current smartphones have difficulties to fulfil the low latency and accuracy requirements of

safety applications.

Although VRUs are the main beneficiaries of the two in-vehicle ITS technology considered in this de-

liverable (BSD and PDS+EBR) it is up to vehicle users to decide whether to purchase vehicles

equipped with these technologies. The development of these in-vehicle ITS will most probably be

funded by the customers of vehicle manufactures that pay for the technologies. As both ITS will have

positive effects on traffic safety and comfort for multiple traffic participants, it is likely that public organ-

izations and insurance companies are willing to compensate the vehicle users. In-vehicle ITS technol-

ogy will increase the EuroNCAP score and may thereby increase the attractiveness and commercial

value of the vehicle. EuroNCAP addresses currently AEB (Automatic Emergency Braking) and BSD

for collision between vehicles, and plans to include pedestrian testing for AEB in 2016. Using the safe-

ty concept as a selling point is also applicable to business models for cooperative ITS systems which

require specific in-vehicle technology.

The deployment of the infrastructure related ITS, IPTS and CAL will most probably rely on public fund-

ing. The European Union and the national and local governments are the primary source of funding for

ITS infrastructure technology. Thus, policy makers like to have a clear description of the benefits of

new technology and are interested in the outcomes it will generate and what it will cost compared to

other ways of achieving the same.

2 of the 10 selected ITS, IVB and GWC are focused on cyclists and involve the deployment of an ap-

plication on a device attached to the bicycle, either a smartphone or a dedicated device. The subscrip-

tion model and the advertisement model might be used in these cases. The time savings achieved by

both systems may be a strong selling point. And the bicycle theft problem opens a market for solutions

such as IVB.

Road map for ITS deployment

This section remarks specific challenges for ITS for VRUs, including: Willingness to pay, Stakeholders,

User acceptance, impacts and benefits, Differences between countries, Differences between user

groups. All in all a private lead is only possible for low cost solutions based on existing devices like

smartphones, or possible for fixed installations in PTWs. In addition, the technical feasibility of solu-

tions is challenging, especially for pedestrians and cyclists. Any significant investments for the benefit

of VRUs will require government involvement, either financial or regulatory, or both.

D2.3


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1. INTRODUCTION

1.1 VRUITS project

In recent years both technological developments and research activities in the fields of Intelligent

Transport Systems (ITS) have primarily focussed on motorised transport to improve safety and eco-

logical (environmental) impacts by advancing equipment of vehicles and infrastructure. The uptake of

ITS applications has assisted in the decrease of road traffic fatalities, particularly amongst passenger

car occupants. However, Vulnerable Road Users (VRUs), such as pedestrians, cyclists, motorcyclists

and moped riders have not enjoyed the same decrease in fatalities. Together, they account for 68% of

the fatalities in urban areas (CARE, 2009). Motorcyclists account for 16% of fatalities, which is much

higher than their contribution to traffic (CARE 2009). While some projects have considered VRUs from

a safety viewpoint, they often aimed at avoiding or mitigating accidents with VRUs by equipping the

vehicle and infrastructure. In the vehicle – infrastructure – human approach of ITS research, VRUs

and their needs are not an active part of the “human” element in the ITS approach.

What is needed? The VRU must become an active, integrated element in the ITS, addressing safety,

mobility and travel comfort needs of VRUs. The EU-funded VRUITS project, which started on

1.4.2013, aims at actively integrating the “human” element in the ITS approach by focussing on needs

of all relevant stakeholder groups into the development and adaptation process of innovative ITS so-

lutions aimed at improving traffic safety as well as the general mobility of vulnerable road users. The

VRUITS project, which is sponsored by the European Commission DG MOVE, places the VRU road

user in the centre, assesses the impact of current and upcoming ITS applications on the safety and

mobility of VRUs, identifies how the usability and efficiency of ITS applications can be improved, and

recommends which actions have to be taken at a policy level to improve ITS safety and mobility. By

applying a multi-disciplinary approach the VRUITS project aims at developing tools to evaluate, field-

test and subsequently improve ITS for vulnerable road users.

The first objective of the VRUITS project is to assess societal impacts of selected ITS applications,

and to provide recommendations for policy and industry regarding ITS in order to improve the safety

and mobility of VRUs. Both ex-ante and ex-post assessment of the applications will be performed in

order to come to a consolidated set of recommendations.

The second objective is to provide evidence-based recommended practices on how VRUs can be in-

tegrated in Intelligent Transport Systems and on how HMI designs can be adapted to meet the needs

of VRUs, and test these recommendations in field trials. Starting from usability study of current ITS

applications, guidelines will be provided on the improvement of the HMI for specific user groups, such

as elderly drivers. A key concept is also the integration of VRUs in cooperative traffic systems, either

through one-way (tags) or two-way communication. The performance and usability of different con-

cepts for the communication between road users in safety critical situations will be assessed. Field

trials for a select number of applications will take place in the Netherlands (Helmond), with an empha-

sis on cyclists and PTW riders, and Spain (Valladolid), with an emphasis on pedestrians.

1.2 Scope and objective of the deliverable

This report describes general scenarios for the years 2020 and 2030 providing developments focused

on road safety trends over time at the EU-level, as well as mobility and comfort trends of VRUs. The

main purpose is to provide input to VRUITS WP3 for the quantitative impact assessment.

Besides a thorough market analysis has been performed on existing ITS as well as relevant trends

and market penetrations, for the applications selected in task 2.3. Information has been collected

about the likelihood of applying these systems in future years, through questionnaires sent to public

administrations in charge of road infrastructure and manufacturers of ITS systems.

D2.3


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Building on the trends and penetration rates obtained, the different business models that are applied

for the exploitation of ITS have been identified and an analysis of the implications linked to applying

each of the different modalities has been made.

Once this analysis has been done, a road map for deployment of the ITS applications selected has

been detailed. This consists of a set of actions in time to promote the use of the ITS and to overcome

the barriers as identified in the questionnaires, starting from a presentation of identified EU and na-

tional ITS action/implementation plans.

D2.3


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2. SAFETY TRENDS

During the VRUITS project, an analysis has been made regarding available data relating to accidents

involving vulnerable road users. As has been outlined previously, there are generally two types of ac-

cident data available with Europe:

In-depth accident data provide very detailed information about specific accidents and can generally be

used to provide information on accident and injury, engineering feedback and standards development

given the very details nature and level of the data that is collected through in-depth crash investiga-

tions. However, this type of data is usually dis-advantaged by the fact that the numbers of cases in in-

depth databases are usually small and statistical representative-ness is sometimes open to question.

Macroscopic data provide cursory information about accidents and are usually based on police inves-

tigations of crashes on the roads in which an injury has occurred. The main advantage of this type of

data is that it is usually representative of the country in which it was collected but the main disad-

vantage is that the level of detail is significantly lower than that that provided in in-depth databases.

Therefore there are advantages and disadvantages of both types of database.

The safety-trends described in this section are based on historical data in terms of what has happened

over the past ten years or so. The data has been modelled using the assumption that current trends in

road casualties will continue. In other words, the rate of decrease will remain more-or-less constant in

the years ahead. The data needs are described as follows;

2.1 Data needs

For the VRUITS data analysis, in order to examine likely future trends in Safety, it has been necessary

to use macroscopic data as the numbers of accident ‘cases’ in this type of data is larger and therefore

the results are generally considered to be more robust. Therefore the EU-CARE data has been used

as it is the database which is thought to be most representative of the EU accident situation.

CARE is a Community database on road accidents resulting in death or injury (no statistics on

damage-only accidents are kept). The major difference between CARE and most other existing

international databases is the high level of disaggregation, i.e. CARE is based on detailed data of

individual accidents as collected by the Member States. This structure allows for maximum flexibility

and potential with regard to analysing the information contained in the system and opens up a whole

set of new possibilities in the field of accident analysis.

EU Member State datasets are integrated into the CARE database in their original national structure

and definitions, with confidential data blanked out. However, transformation rules are implemented in

the CARE database in order to increase data compatibility and thus enhance the functioning of the

system.

2.2 Compilation of accident data

The CARE database has been analysed to predict the likely changes in road casualties during future

years. However, assumptions have been made when making these predictions. The main assumption

is that there will be no effect of the introduction of ITS systems. In other words, the trends in road

casualties will continue as the effects of new ITS systems cannot be calculated given that (a) their

effects remain unproven; and (b) the details with regard to uptake, market penetration and user

acceptance are still far from clear.

D2.3


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2.3 Road safety trends and forecasts 2002 to 2030

2.3.1 Results

Figure 1, Figure 2, Figure 3 and Figure 4 contain details of historical data from 2002 to 2012. The

trend in accident numbers of all severities is shown in Figure 1. As can be seen, there is a significant

decline in the numbers of accidents overall with car occupant casualties showing a modest decrease.

However the decline in accident numbers for the VRU’s is much less pronounced with bicycle and pe-

destrian casualties remaining relatively constant.

Figure 1 Trends in numbers of accidents (all severities), 2002 to 2012

The trends in fatalties from 2002 to 2012 are shown in Figure 2 below. As can be seen, passenger car

fatalities have declined steeply over the period whereas the decline for the VRU groups are again

much less pronounced. With bicycle fatalities showing a negligible decline. The trend in fatalities is

similar to that for Serious Injuries (Figure 3) although the rate of decline is perhaps not as pronounced

for passenger car users whilst the numbers of VRU’s who are Seriously Injured does not change

between 2002 and 2012. The trend for ’Slightly Injured’ casualties (Figure 4) is similar to those

observed for Fatal and Seriously Injured road-users although bicycle and pedestrian casualties appear

to have increased slightly during the period.

D2.3


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Figure 2 Trends in numbers of accidents (Serious Injury), 2002 to 2012

Figure 3 Trends in numbers of accidents (Fatalities), 2002 to 2012

D2.3


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Figure 4 Trends in numbers of accidents (Slight Injury), 2002 to 2012

In the following figures, the data have been analysed to predict the likely numbers of casualties by

transport mode for each accident severity in the event that the rate of decrease observed between

2002 and 2012 continues. This has been conducted using regression analyses.

Figure 5 shows the likely trend in all road-user fatalities assuming that the current trends in road casu-

alty numbers remain the same until 2030. As can be seen from the figure, car occupant fatalities will

fall to just around 6,000 from the 2002 figure of 35,000 which represents a dramatic decrease. How-

ever, the predicted decrease for the VRU groups is not so dramatic.

Interesting trends are shown in Figure 6 which shows the predicted number of accidents for each VRU

group. As can be seen PTW accidents are predicted to decrease dramatically whilst the numbers of

bicycle accidents are actually expected to increase.

Figure 5 Predicted numbers of Fatalities by 2030 by Road-user Group

D2.3


7

Figure 6 Predicted Numbers of Accidents by 2030 for the VRU Group

Figure 7 below shows the predicted numbers of VRU fatalities by 2030 assuming that the current

trends remain constant and that there is no system intervention during this period. The trends for pe-

destrian and PTW user groups are predicted to be similar whilst the trend for the bicycle users shows

a decrease which is not to the same extent as the other road-users. Even despite this decrease, the

model predicts that over 5,000 VRUs will be fatally injured during 2030 assuming that no effective

countermeasure is introduced.

Figure 7 Predicted Numbers of Fatal Accidents by 2030 for the VRU Group

Figure 8 shows the predicted numbers of ‘Serious’ road accidents by road-user group by 2030. As can

be seen from the figure, the decrease in seriously injured car occupants is substantial whilst the de-

D2.3


8

crease in VRU accidents is much less pronounced. The data for the VRU group have been analysed

separately (Figure 9) and it can be seen that numbers of ‘Serious’ bicycle accident casualties are ex-

pected to surpass pedestrian accidents by 2030.

Figure 8 Predicted Numbers of Serious Road Accidents by 2030

Figure 9 Predicted Numbers of ‘Serious’ Road Accidents by 2030 for the VRU Group

Finally the trends for ‘Slight’ accidents are shown in Figure 10 and Figure 11. Again, the trends in pre-

dicted car occupant ‘Slight’ casualties suggest a raid downward decrease in numbers with VRU casu-

alties expected to decrease much less dramatically. When VRU casualties are analysed separately

(Figure 11), it can be seen that bicyclists are expected to be the most frequently injured VRU at the

‘Slight’ injury level by the year 2017.

D2.3


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Figure 10 Predicted Numbers of ‘Slight’ Road Accidents by 2030

Figure 11 Predicted Numbers of ‘Slight’ Road Accidents by 2030 for the VRU Group

D2.3


10

3. MOBILITY AND COMFORT TRENDS

Based on the available findings produced in course of the VRUITS project and a literature search,

available data on the mobility and the comfort of vulnerable road users was collected. In addition po-

tential trends in these regards were identified based on current studies with focus on future issues and

needed measures and developments in different areas such as infrastructure, technology, society, etc.

The goal of producing an overview on available empiric data on the characteristics of behaviour and

the comfort aspects of vulnerable road user mobility was to establish present and future scenarios

where ITS solutions can support VRUs. Both aspects, general mobility behaviour and comfort aspects,

need to be taken into account as relevant factors besides safety when discussing actual technology

potential of ITS.

The following chapter outlines definitions of mobility and comfort, as identified in VRUITS deliverable

D2.2, and provides insight into the availability of empiric date to measure these concepts. In addition a

forecast and potential trends are discussed based on found data and studies directly focussing on the

issue of future VRU mobility.

Overall actual definitions and used concepts and the corresponding data collected in view of the mo-

bility and comfort studies found in course of the literature search process vary quite strongly. While

some of the national travel surveys are providing recent data there are European countries which have

no up-to-date assessments available only providing limited insight into the actual mobility behaviour of

VRUs. While relevance to the current mobility behaviour of VRUs is one major issue, comparability is

another problem usually encountered when discussing mobility data. These limitations are even more

pronounced when discussing data on the comfort of vulnerable road users. Especially the definition of

the concept of VRU comfort has already been identified as one of the main limiting factors when look-

ing for available empirical data.

Trends in the mobility of the different vulnerable road user groups are strongly related to regional dif-

ferences, with weather and seasonal changes being especially relevant for VRUs, car dependency

and available modal choices. In addition actual and perceived safety are expected to play an important

role, especially in view of the effects of demographic change on travel patterns. Looking at comfort

developments the interplay between safety, mobility and comfort and the influencing factors outlined in

previous VRUITS reports (D2.1, D2.2) become apparent. Future developments will strongly be de-

pendent on individual perceptions of safety, uncertainty connected with travel and stress and

measures introduced on macro and micro levels to address them.

As already stated in the second deliverable of the VRUITS project, recent data focussing on the actual

mobility of vulnerable road users that not only characterizes VRU mobility on a national level but al-

lows for country comparisons between European countries is scarce. Looking at the availability of em-

piric data on the comfort of different vulnerable road user groups the situation is even more problemat-

ic. In this regard only a handful of projects are directly focussing on the comfort issue by assessing all

relevant dimensions of the issue, although mostly only addressing one or two of the vulnerable road

user groups.

3.1 Data needs

To be able to identify actual data needs in regards to mobility and comfort actual mobility and comfort

concepts need to be discussed, which not only take all relevant dimensions into account but also out-

line the variables needed for a comprehensive assessment.

In course of the development of the ITS assessment methodology the following definitions proved to

be most applicable in view of general VRU mobility and comfort and are therefore most relevant for

the scenario development:

D2.3


11

Vulnerable road user mobility as used in course of task within the VRUITS project is defined as:

“(…) any form of outside (meaning out of house) movement based on the identified soft

transport modes: walking, cycling or motorcycling. These forms of movement are defined by

trips from a starting point to a destination in order to conduct an out of house activity.”

(VRUITS D2.2).

The definition used to explicate vulnerable road user comfort in travel is based on Slater (1985) as:

“(...) a pleasant state of physiological, psychological, and physical harmony between a human

being and the environment” (Slater, 1985: p. 4).

This definition is especially relevant in view of the assessment of ITS technologies as it is relating to

the individual experiences, attitudes and requirements to not only travel in safe but also a pleasant

way.

The data presented here is based on the above concepts as they have also been a core element of

the development process of the VRUITS assessment methodology to be applied in course of the

qualitative and the quantitative assessment processes.

3.2 Compilation of mobility and comfort data

As is apparent from the above definition of mobility used in the context of VRUITS, the data needed to

discuss the general mobility of vulnerable road users is strongly relying on variables of exposure. A

comprehensive list of mobility related variables which are defining the concept of mobility used in this

context are the following (Sammer et al 2011):

Region (urban, rural, etc.)

Number of trips per person

Mode of transport

o Main mode of transport (for a specific trip [purpose])

o Modal-Split (of all used modes on a trip),

Source trip purpose (goal of the previous trip).

Trip duration

Route choice

Travel distance

Travel length

Travel speed

Time spent on travelling, duration

Number of journeys

Departure time/arrival time

The actual compilation of data considered in course of the assessment process are as follows and

cover a broad range of travel behaviour variables, starting out with the actual modal choice, route

choice behaviour and exposure data.

Mode of transport

Route choice

D2.3


12

Travel distance

Travel length

Travel speed

Time spent on travelling, duration

Number of journeys

Departure time/arrival time

Based on these indicators actual mobility behaviour of the different vulnerable road user groups con-

sidered (bicycles, pedestrians. motorcyclists) can be characterized and potential impacts of ITS solu-

tions need to be measured based on these variables.

To assess the current mobility behaviour of vulnerable road users, mobility data is strongly focussing

on exposure. Comfort data is mainly assessing psychological factors of mobility which are strongly

related to the individual perceptions of vulnerable road users. These aspects are usually identified and

discussed in conjunction with external conditions including available infrastructure and environmental

conditions. These aspects are again very strongly dependent on regional and seasonal differences.

Scarcely available literature on empiric comfort data of different vulnerable road user groups is focus-

sing on a variety of different indicators which are not only relating internal and external conditions, but

are also discussing “physiological, physical, social and psychological reactions” (Ovstedal & Ryeng,

2002: p. 2). These assessments are very heavily relying on psychological indicators that relate to indi-

vidual perceptions of the environmental, infrastructural and situational conditions which directly affect

road user comfort. While the different dimensions that need to be taken into account when discussing

comfort of vulnerable road users comprehensively are taking assessments of the built environment

and factors such as attractiveness into account (Ovstedal & Ryeng, 2002), the indicators used in

course of the scenario development are limited to strictly mobility relevant comfort factors. In order to

be able to assess ITS impacts on vulnerable road user mobility the following four indicators were iden-

tified for assessment:

Workload related to travel

Stress related to travel

Uncertainty related to travel

Feeling of safety in relation to traffic

As these indicators cover a variety of different concepts hardly available in one scientific study repre-

sentative of at least one European country, there is hardly any empiric data that can be used for coun-

try comparisons.

The measurement of these indicators of comfort varies from available study to study, with only in

some cases specific definition of each of these concepts, which can be problematic as i.e. stress and

uncertainty can be directly related and influencing each other. As these aspects are measured based

on survey methodologies the already above mentioned study of Ovstedal and Ryeng (2002) used the

following rating system for assessing individual safety perceptions on a specific pedestrian trip:

Figure 12 Rating of trip specific pedestrian safety perception (Ovstedal & Ryeng 2002, p. 88)

All of the above presented indicators to assess mobility and comfort are discussed in view of the dif-

ferent vulnerable road user groups (pedestrians, bicyclists, motorcyclists) as well as motorized traffic

D2.3


13

(car drivers and truck drivers) as certain systems are directly or indirectly affecting car or truck drivers.

In addition to the actual transport mode scenarios affected user groups are differentiated by age group

and special mobility needs (including children, elderly, and people limited mobility).

To be able to assess ITS effects regarding mobility and comfort, actual circumstances of system use

such as weather and lighting conditions as well as situations and locations in traffic where ITS sys-

tems are used (i.e.: intersections, links, general traffic network).

3.2.1 Mobility data

Looking at studies which already assessed data available on the mobility of vulnerable road users in

Europe show how concepts of mobility (i.e.: definition of vehicle types, etc.) vary as well as the years

mobility data have been collected. Only few countries in Europe conduct repeating travel surveys with

fixed periods, which provide insight in changes in mobility patterns and allow for comparing trends of

different road user groups.

Available literature providing insight into studies collecting mobility data is limited. Nevertheless in

1998 the OECD and the Scientific Expert Group on the Safety of Vulnerable Road Users (RS7) con-

ducted a comprehensive study outlining vulnerable road user mobility not only discussing available

data in European countries but also in Australia, New Zealand and Japan.

Table 2 Available comparable mobility data in OECD countries in 1998 (OECD, 1998, p. 225).

The OECD summary of available mobility surveys outlines one of the biggest issues regarding mobility

data, which is comparability, as the above table only lists those surveys which allowed for country

comparisons based on available data.

A more recent summary of avilable national travel surveys is found in the PQN final project report

(2010), providing again insight in the age of the data available in European countries, as well as into

sample sizes and the actual information collected.

D2.3


14

Table 3 National travel surveys available 2010 (Monterde i Bort et al. 2010, p. 45)

D2.3


15

As can be seen above exposure data collected varies heavily starting with the period the data is col-

lected as well as the actual trip characteristics which are considered. In addition considered age

groups and sample sizes vary, as can be expected. Nevertheless the data provided by the different

national travel surveys allows for country comparisons based on modal choice and trip lengths.

Nevertheless there have been a number of studies working with available OECD mobility data, detail-

ing modal choice, trip lengths and duration of trips. While there are studies going in-depth for a single

mode when analysing mobility data, there is a lack of research on actual country and mode compari-

sons providing comprehensive insight in country specific differences, which would be especially inter-

esting in regards to VRU mobility.

Looking at relatively current data of OECD countries (David R. Bassett, Jr. et al., 2008, p. 799) in view

of modal choice including soft transport modes (walking, cycling and transit) it can be seen that the

percentage of walking trips in Europe is comparatively high compared to the USA, Australia and Can-

ada, with especially Switzerland and Spain showing the highest levels of walking trips. Cycling trips

account for a lower level of overall trips with Denmark (15% of trips) and the Netherlands (25% of all

trips) traditionally leading in Europe.

Figure 13 Percentage of trips by modes in Europe, Canada, USA and Australia (David R. Bassett, Jr. et al., 2008, p. 799)

Taking transit into account shows the highest percentage of trips in Latvia and Austria, followed by

Spain and Sweden. Overall comparing European trip percentages in view of used modes to the USA,

Australia and Sweden shows a more soft-mode oriented kind of mobility with only Ireland exhibiting

comparatively low percentages of walking and cycling trips.

D2.3


16

Table 4 Modal Split by age groups in the Netherlands (SafetyNet, 2009, p. 8)

Taking also motorcycling in conjunction with age groups into account, which is strongly related to age

limitations, it can be seen that there are significant regional differences. While both mopeds and mo-

torcycling is effectively only relevant in the age groups between 12 and 24 years of age in the Nether-

lands. As the numbers of trips travelled on motorcycles is generally low, with decreasing numbers in

the recorded years, the different powered two-wheeler classes are mostly combined to one group. The

differences between different PTW classes are especially obvious between the northern European

countries and the southern parts of Europe, with comparatively more mopeds registered in southern

Europe.

Figure 14 Road passenger transport in the EU25 (EU transport in figures. 2012)

Overall powered two-wheelers account for only 2-3% of the modal split in Europe (EU transport in fig-

ures. 2012, p. 47).

Taking trip lengths and times spent in travel into account yields differences between urban and rural

areas as is to be expected, especially in context of the soft transport modes.

Walking trips account for the highest percentages in urban areas and for shorter trips, usually below 3

km, with cycling trips of up to 4km in the more densely populated areas in Europe (Berge and Peddie.

2001, pp. 5). OECD data shows that cycling trip distances generally vary between European countries

and vary between around 2 km and up to 4km in Finland (OECD 1998).

D2.3


17

Figure 15 Average trip length for cycling (kilometres) (OECD. 1998, p. 50).

Walking trip distances vary as well with shorter trips in the UK (around under 1km) and up to 3km in

Finland (OECD 1998).

Figure 16 Average trip length for cycling (kilometres) (OECD. 1998, p. 50).

More recent data from 2006 confirm these findings (OECD 2006), with walking trips still ranging be-

tween 2 and just under 2km, with Sweden and Finland exhibiting the longest walking trips in urban

areas and Austria and Switzerland the shortest in comparison.

While data on modal choice and trip length is readily available, there is a bit of a lack of current infor-

mation on walking and cycling speeds as well as on the actual duration of these trips.

The figure below provides insight in country comparisons (Europe, New Zealand, USA) in regards to

average duration of walking trips in the countries where data was available. As can be seen there are

actual differences between countries with the Scandinavian countries and Germany having the longest

walking times, which also correlate with actual walking distances (Guro and Peddie. 2001). Guro and

Peddie who analysed these data concluded the following in regard to walking speeds and distances:

“Comparing the distances with these durations of pedestrian trips shows that people in the

OECD-countries walk at a speed of between 56 and 77 meters per minute. If these figures are

D2.3


18

reliable, it is interesting to note that the people walking in Austria and Switzerland, where they

have the highest share of walking and the shortest trips, have the lowest average walking

speed of all (56 m/min).” (Guro and Peddie. 2001, p. 11)

Figure 17 Average duration of a pedestrian trip in minutes (Guro and Peddie. 2001, p. 11)

As especially walking is often used in course of multi-modal trips, kilometres per number of journey

and per person also need to take the usage of other modes into account. The PQN project (PQN,

2010) outlined these aspects as a correct assessment of actual walking trips needs to also consider

an underrepresentation on walking trips in view of other used modes (see table below).

Table 5 Walking and estimated figures for multimodal walking in the Netherlands in 2007 (PQN 2010)

Based on such estimates distances covered when using metro, bus, or train connections can be taken

into account to more comprehensively represent actual walking behaviour.

Christensen and Vázquez (2013) provide a comprehensive overview over 12 European countries and

exposure data for different travel modes, harmonized for comparison. Generally these results based

on national travel surveys show again national differences in regards to vulnerable road user mobility.

D2.3


19

Figure 18 Distance, time use, and number of trips per traveller per day, distributed at modes (Chris-tensen and Vázquez. 2013, p. 7)

As can be observed based on the above figures travel times and trip distances are correlated, with

longer trips equating to shorter times in travel due to the use of motorised transport modes. Especially

Spain exhibits a high level of walking trips, both in regards to walking distances as well as time spent

in travel.

In addition VRU mobility is strongly dependent, among others, on trip purpose, walking and cycling in

conjunction with other modes (i.e.: public transport, or passenger car), urbanization level, gender and

age. Looking at mobility survey data from Germany (MID 2008) and Finland (National Travel Survey

2010-2011) in view of trip purposes provides vital insight into differences regarding both mobility be-

haviour and data collection (see figures below).

D2.3


20

Trip purpose

Work

15%

Education

4%

Business

7%

Shopping

39%

Free time

35%

Trip purpose

Work

18%

School, studies

7%

Business

4%

Shopping, personal

business

34%

Visits

11%

Summer cottage

1%

Other leisure

25%

Figure 19/20 Trip purpose by mode – Germany/Finland (own illustration)

Actual trip purposes are vary only slightly looking at the figures above for Germany and Finland, nev-

ertheless mobility data is limited, without providing insight into actual modes used for given trip pur-

poses. While conclusions cannot be drawn in regards to different modes data from the Finnish Nation-

al Travel survey provides insight into trip purposes by actual modes. In addition limitations of available

data found in course of the mobility survey collection process are especially problematic in view of

modal split in regards to non-motorized transport. A number of surveys do not distinguish between

pedestrians, cyclists and other forms of human powered transport making comparisons focussing

solely on VRU impossible. Moreover not all data is presenting mobility behaviour in view of gender or

age groups, only providing information on a general country level.

While the data presented in Appendix C. provides an overview over European regions and even al-

lows for comparisons on country levels, the limitations encountered in the data search process are

apparent. While accident data on a macro level is readily available on a European level, such basis for

assessments does not exist for mobility behaviour data. There are research projects such as the

COST project SHANTI (http://shanti.inrets.fr/index.php), which is specifically focussing on data acces-

sibility and cross country linkage of mobility and travel data, there is not yet any database available

yet.

3.2.2 Comfort data

As outlined above actual comfort data is hard to come by on a European level, especially studies

where all dimensions of comfort are addressed are scarce. Generally data on comfort, when available,

is very specific to the assessed road user group, with a strong focus on regional aspects relating to the

usability and quality of a certain vulnerable road user environment.

Generally the following aspects need to be considered when assessing comfort, which cover the indi-

vidual experiences in traffic in view of:

Workload related to travel

Stress related to travel

Uncertainty related to travel

Feeling of safety in relation to traffic

http://shanti.inrets.fr/index.php

D2.3


21

As can be seen collected data is usually based on surveys to collect subjective assessment identifying

issues in traffic and the built environment. In addition differentiations between different user groups

depending on their specific mobility and comfort needs need to be applied in course of a comfort as-

sessment. In this regard older and younger road users have very different abilities when it comes to

task competences in traffic leading to a difference in experienced workload and stress.

As outlined in the aforementioned PROMPT study specific aspects that are relevant for assessing pe-

destrian comfort can be as follows (Ovstedal and Ryeng. 2002, p.3):

Lack of places to rest, lack of convivial places: no place for recreation when pedestrians are

tired, ways seem longer because of unattractiveness

Bad air quality, bad smells (gas emissions or other disturbing smells); high

noise level: distraction, bad for the health

Socially insecure places: fear, avoidance of certain places

Lack of public toilets: reason for staying at home; restriction of mobility

Lack of protections against weathering: becoming wet, dirty

Badly illuminated sidewalks: fear, danger of falling; detect hindrances in time

Lack of signs, information points, guiding systems for visually impaired people: to find the right

way, to move safely

Data available for pedestrian transport produced in this research project covers six countries and

therefore constitutes one of the better resources for cross country comparison in regards to comfort

data.

Table 6 PROMPT Case study sites (PROMPT 2002)

Country data available Regions Sample size

Finland City centre/suburb 199

France Residential area 119

Italy Residential area/suburb 159

Norway City centre 180

Switzerland Residential area/suburb 131

Belgium City centre/suburb 304

Available data needs to be based on surveys with each vulnerable road user group, with aspects such

as age, groups with specific needs in view of comfort (i.e.: children, elderly, people with mobility im-

pairments) being addressed as comfort is, as already pointed out above a very complex concept con-

sidering individual perceptions and attitudes into account. A profile of pedestrian comfort assessed for

people walking in Trondheim Norway is seen in the figure below and characterizes the comfort data

available as well as the methods generally used to produce this data.

D2.3


22

Figure 21 PROMPT study results from Trondheim (PROMPT 2002)

As methods to collect comfort related data vary greatly, comfort assessments are mostly focussing on

very specific locations or situations in traffic where regional differences and certain characteristics of

the assessment sites play an integral role. The figure below based on Sarkar assessment of pedestri-

an quality conditions in urban walkways and activity centres (2002) highlights the data limitations as

data available is also strongly dependent on the timeframe, as for instance weather conditions, noise

levels and pollutions levels are changing and do not represent constant variables.

Figure 22 Comfort assessments on Chestnut Street between 15th and 18th Street.

The above figure represents the results from a comfort assessment of the walking facilities on Chest-

nut street on a given section, with assessed factors covering pollution, noise, weather protection and

accessible activities and seating opportunities. Thus conclusions can only be drawn on a regionally

very limited level with no data available for generalization or even for country comparisons.

D2.3


23

While data on workload and stress of vulnerable road users is scarce, the concept of subjective safety

assessments is nothing new with a number of studies available outlining the current situations in some

European countries. Nevertheless to be able to provide a quantitative level of comfort of different VRU

groups, only accessible data on a comparative level can be used.

While the PROMPT study, as one of the only currently available in regards to VRU comfort, is only

focussing on pedestrian comfort, without taking PTWs and bicyclists into account it is highly problem-

atic to conclude on a general level. One opportunity to overcome these issues could be to rely on

safety data of VRUs as one indicator for general comfort. To approach comfort assessment on a

quantitative level a combination of both available safety data and the collected accessible mobility da-

ta were ranked on an experimental basis to provide a view on comfort, based on quantitative data.

While this approach disregards the above mentioned comprehensive discussion of comfort based on

subjective assessments, it relies on trips per person (based on accessible mobility surveys) and se-

verely injured and killed persons (based on European CARE data).

Based on available studies on modal choice and subjective assessments, which have shown that

modal choice is strongly dependent on behavioural indicator variables such as comfort (Johansson et

al 2005), it can be expected that the number of trips per mode is dependent on the actual comfort dur-

ing travel. While there are other indicators for mobility behaviour such as trip length and duration of

trips, these are strongly dependent on regional and geographical differences. By using actual number

of trips per country where data is available, a better estimation of the relevance of this mode is possi-

ble. For the sake of estimating the comfort of VRUs quantitatively, a higher number of trips is expected

to represent a higher level of comfort for a given mode.

To also consider the safety aspect in establishing comfort levels for a sample of European countries,

accident data available for the target year 2008 were used based on CARE data. There are studies

suggesting that safety perceptions and the actual safety of a traffic system, influence mode choice and

route choice (Noland, 1994; Parkina et al. 2006). While there is sample research on the differences

between objective and subjective safety, with objective safety being represented by actual accidents

and subjective safety being individual assessments of traffic safety, this approach is based on the as-

sumption that objective traffic safety represents a general level of safety which in turn affects subjec-

tive safety.

To establish a comfort level per mode and country number of trips and numbers of injured and fatali-

ties from Germany, the United Kingdom, Estonia and the Netherlands served as basis. As needed

mobility data and accident data was only available for these four countries for 2008, this sample was

chosen as basis for comparison.

The actual comfort level as ranking is based on the statistical number or trips per mode until an acci-

dent happens in a given country. The higher the number of trips until an accident occurs the higher the

level of comfort. The lower the final comfort score the lower the score the lower the comfort level per

mode per country. The scoring-points were structured based on quartiles.

In the following table comfort for pedestrians, cyclists and PTWs is ranked by country, based on num-

ber of trips and accident data (for an overview of data used for ranking see Appendix D.

Table 7 Comfort ranking for pedestrians, cyclists, PTWs by country

Pedestrian Cyclists PTWs

UK 1 UK 1 DE 1

EE 3 DE 3 NL 3

DE 4 EE 4 UK 4

NL 5 NL 5 EE 5

D2.3


24

Based on this concept of comfort, which is strictly based on mobility and safety data, pedestrian and

cycling comfort ranks the highest in the Netherlands, and the lowest in the UK. Comfort for PTWs

ranks the lowest in Germany and the highest in Estonia. Based on the data used for establishing the

comfort rating, pedestrians and cyclists in the Netherlands are performing more trips until an accident

happens in comparison to the other countries, while in the Estonia and the United Kingdom PTWs are

travelling more until an incident occurs.

The following figure shows an overall comfort ranking for all three modes, for the Netherlands, Esto-

nia, Germany and the United Kingdom.

COMFORT RANKING

13

12

8

6

0

3

6

9

12

15

Netherlands Estonia Germany United Kingdom

Figure 23 General VRU comfort ranking by country

As can be seen in the cumulative VRU comfort ranking, the Netherlands rank the highest with a score

of 13 (of maximum 15) points and the United Kingdom scores the lowest with 6 points.

While the above presented model for ranking comfort for different modes in different countries, based

on scoring of performed trips and accidents, allows for country comparisons, it lacks all subjective as-

sessments of the comfort models discussed within VRUITS. In addition aspects such as environmen-

tal and infrastructural factors or individual requirements in view of satisfactory travelling are not con-

sidered due to the lack of comparable data. Ideally a quantitative assessment of comfort would take

these variables into account leading a more complex model of comfort allowing for a more effective

assessment than the proposed rather rudimentary approach.

However as comfort is mostly regarded as an aspect of either safety, or mobility, this approach incor-

porates both objective variables into a ranking that allows for a comparisons between countries (where

the needed data are available for a given time period).

3.3 Mobility and comfort forecast

Especially in view of general mobility forecasts data is available for all road user groups. Main focus of

trend analyses presented in different studies is generally focussing on modal spilt with potential for

sustainable mobility behaviour and corresponding reductions in CO2. While safety trends for different

road user groups are readily available for Europe, general mobility trends detailing expected changes

in walking distances, times spent in traffic, etc. are fairly limited. Nevertheless general trends in land

use, spatial planning and policy objectives on both national and European levels hint at potential de-

velopments in the area of vulnerable road user mobility.

D2.3


25

Generally a number of mega trends are to be distinguished which are expected to influence mobility

patterns in general in the coming years up until 2030.

A more multi-modal and intermodal mobility will change modal splits where soft transport

modes are a viable alternative. General mobility behaviour will increasingly entail the use of

different transport modes. Trips are expected to be more intermodal encompassing a variety

of modes until a destination is reached.

Overall reduced car use, due to higher fuel costs and advancements in spatial planning. In

addition the numbers of cars especially in urban areas are expected to be decreasing due to

the fact that there is a trend towards sharing transport options instead of owning a car oneself.

The increased relevance of e-mobility for both short trips and freight and commuter traffic will

also impact the modal choice for short trip mobility towards soft modes especially in urban

contexts.

Overall general expectations are strongly focussing on the urban areas in Europe where technological

innovations in conjunction with spatial planning and improved public transport options help to develop

more car-free mobility profile for a broader range or road user groups. This in turn is expected to

change the modal split in the urban centres sustainably towards walking, cycling and also PTWs.

3.3.1 Mobility forecast

Available mobility trend analyses are expecting an increase in general mobility of all road user groups

with passenger transport rising consistently in the next 15 years (DG TREN 2009). Besides long dis-

tance travel, including air traffic, passenger car and PTW transport together will also in future scenari-

os be of significant importance in view of overall transport in Europe.

Figure 24 Projection of the passenger transport volume in EU-25 (DG TREN 2009)

When taking changes in modal change including different vulnerable road user groups into account

available data is not as readily available. Expected modal share in France for instance is expected to

change in favour of soft modes including public transportation. Especially for people without access to

cars public transport and motorcycles are expected to be the most important substitutes. Nevertheless

D2.3


26

also in households with at least one car public transport will still be one of the more important modes,

followed by walking.

Figure 25 Modal shares in France in 2010 and 2020 according to three cases of motorization (Chevalier and Lantz 2013)

As mobility in general is strongly dependent on policy measures introduced to influence economic,

ecologic and social improvements over longer periods of time, these changes will strongly impact how

mobility conditions for vulnerable road users will be shaped. Following the European status report on

road safety (2009) most relevant measures to actually support modal change towards soft transport

modes are focussing on infrastructural aspects (bicycle lanes, footpaths) and generally traffic calming

measures (see figure below).

Figure 26 Policies to promote walking and cycling (European Status Report on Road safety 2009)

As these policies are also strongly influencing factors in regards to the experienced comfort by pedes-

trians and bicyclists, especially in view of subjective safety as well as workload and stress, sustainable

D2.3


27

improvements are correspondingly to be expected. Thus spatial and urban planning activities focus-

sing on both new developments and adaptations in the built traffic systems will be highly influential

factors for the long-term development of vulnerable road user mobility.

Based on current policies on a European level and expected road safety developments among all dif-

ferent road user groups, a variety of scenarios seem to be possible considering a time frame until

2030. Tight (2011) developed a three-scenario scheme taking these developments into account and

presented a correspondingly adjusted modal split (see table below).

Table 8 Modal split and three scenarios for Europe in 2030 (Tight 2011)

Starting with the base year of 2006 and the respective modal split of the UK, the first scenario repre-

sents a best case scenario in view of ongoing policies and projects towards an improvement of the

situation for urban planning with vulnerable road users in mind. A consequent application of best prac-

tices in Europe would already yield significant improvements for walking, cycling and public transport

use.

The second scenario presented by Tight is going one step further, expecting a more socially fair

transport system and behaviour. The transport system is focussing on alternatives to car use strongly

increasing the shares of walking and cycling, with decreasing numbers of car holders in the system.

The final scenario represents a transport future which is characterized by modern land use and plan-

ning, which is focussing on shorter trip distances and modern transport infrastructure. In this forecast

the car is basically non-existent or not needed in urban areas, as most rips can be covered by walking

and cycling, or other innovative human-powered vehicles. Therefore walking and cycling have become

the most important modes of transport and together constitute a share of 80% in the modal split.

Another more complex model outlining expected kilometres in view of four different scenarios provides

insight into model split for all modes, including human powered transport (see Table 9).

D2.3


28

Table 9 Forecast of passenger kilometers (Graham 2005: 30)

Mode of transport 1995 Unrestricted growth

Sustainable growth

Business as usual

Sustainable bal-ance

Car 3005 7486 5146 6089 3405

Percentage 69% 72% 64% 72% 59%

Bus 289 371 342 274 298

Percentage 7% 4% 4% 4% 5%

Human-powered 171 235 255 374 390


Powered two wheeler 71 145 344 102 290


Rail 480 917 1073 788 763

Percentage 11% 10% 13% 9% 13%

Air 314 1310 952 871 615

Percentage 7% 12% 11% 10% 10%

Total 4330 10464 8111 8499 5761

This model is based on economic factors influencing European freight and passenger transport up

until 2030. This model seems to provide a good basis for the assessment of technological impact as

the four proposed scenarios (see figure below) already integrate technological and infrastructural in-

novations focussing on actual road user behaviour unto account. The sustainable scenarios for in-

stance are already implying a decrease in car use due to new forms of micro transport especially in

urban areas (Graham 2005: 29). On the other hand the unrestricted model and the sustainable growth

models take a rapid increases in deployed ITS as well as urban transport into account.

Figure 27 Models for mobility forecasting (Graham 2005: 29)

Although this model does not differentiate between pedestrian and cycling (kilometres) it is one of the

most comprehensive approaches to discuss actual expected passenger kilometres up to 2030. As can

be seen in the figure below, modal split is expected to increase car traffic in the unrestricted and busi-

ness as usual models. As can be expected based on the definition of the models in view of actual sus-

tainability, motorised traffic is expected to be the highest in these scenarios. Soft transport modes on

D2.3


29

the other hand, including walking, cycling and PTWs are expected to be the highest when European

economies develop more sustainably.

Modal Split Forecast

0%

10%

20%

30%

40%

50%

60%

70%

80%

1995 Unrestricted growth Sustainable growth Business as usual Sustainable balance

Car

Bus

Human-powered

Powered two wheeler

Rail

Air

Figure 28 Modal Split forecast for 2030 (Graham 2005, own illustration)

In all four scenarios general mobility is expected to increase significantly in the next 15 years. Depend-

ing on the given scenario, VRUs (pedestrians, bicyclists and PTWs) are still expected to be on a low

level compared to the main mode of transport, which remains the car. Nevertheless in case of an ideal

sustainable development (scenario 4) pedestrian and cycling trips are expected to make up 7% of

travelled kilometres in Europe.

While these data provide insight into general modal split and also take vulnerable road user mobility

into account, they only provide insight into modal split and travelled kilometres while not differentiating

between pedestrians and cyclists.

3.3.2 Comfort forecast

Forecasting travel conditions relating to actual comfort of vulnerable road users in traffic proves to be

difficult. Nevertheless estimations can be based on developments in the built environment targeting

aspects which have an influence on the perceived safety, the workload regarding the mobility task and

the potential for unclear and uncertain situations.

While there are no studies available focussing on pedestrian, cycling and PTW comfort specifically

preventing the presentation of direct trends in this regard, developments, policies and specific

measures expected to influence VRU comfort are shortly outlined and presented. As most of the

available measures aiming at level of service are developed and applied on national, or more often

regional levels, rather than on EU levels, a selection of most promising solutions which all also include

expected effects based on empiric evidence are discussed.

The PROMISING (SWOV 2001) project outlines the ten most promising measures for increasing gen-

eral mobility for the different vulnerable road user groups, which also relate to the above stated sub-

categories of comfort. A selection focussing on VRUs is found below:

A separate network of direct routes for pedestrians and a separate network of direct routes for

cyclists.

A categorisation of roads to separate flow traffic from distribution traffic and access traffic.

Area-wide speed reduction apart from roads with a flow function for motorised traffic.

D2.3


30

Implementation (and development) of infrastructure design standards for pedestrians, cyclists

and motorised two-wheelers.

Right-of-way rules and regulations for cyclists and pedestrians in urban areas and technical

measures that support right-of-way and stimulates perception and anticipation.

Review of traffic rules to consider privileges for motorised two-wheelers in relation to car driv-

ers.

A graduated or intermediate licensing system for young car drivers and motorised two-

wheelers.

Education that focuses on a considerable and respectful attitude to other road users.

Injury protection by design of cars and heavy vehicles. (SWOV 2001: 91-92)

As can be seen the identified high-potential solutions touch on aspects of both objective and subjec-

tive safety, expectations in conjunctions with visibility, and regulations and infrastructure design ap-

proaches which directly address workload and stress related factors for vulnerable road users. In this

regard the development of specifically adapted infrastructure is expected to have the most influence

on the general usability and comfort for vulnerable road users in coming years. The PROMOSING pro-

ject therefore suggests a hierarchy of road types aiming for the ideal environment for VRUs (SWOV

2001: 13):

through-traffic route with a speed limit of 70km/h and only grade-separated crossings;

main street or urban arterial road with speed limit of 50km/h and, in some areas 30km/h;

residential street with a speed limit of 30 km/h;

walking-speed street;

car-free areas for pedestrians and cyclists.

In general comfort of vulnerable road users is expected to be strongly dependent on the space availa-

ble especially for pedestrians and bicyclists as a number of critical scenarios negatively impacting

workload, stress and uncertainty as well as the subjective assessment of safety relate to situations

where traffic lanes are shared between different road user groups.

The figure below outlines on the left side the share of space in the Stockholm road network as of

2012. On the right the actual usage of the available space is presented characterizing how space is

shared between road user groups in a modern road network.

Figure 29 Land use of the road network of the city of Stockholm (City of Stockholm 2012: 19)

D2.3


31

There is still a high level of space shared between pedestrians and bicyclists and motorised traffic in-

cluding public transport vehicles which in turn leads to higher demands for safely and comfortably

travelling in high density areas.

The table below provides insight into current land use and expected changes up until the year of 2030

including facilities for pedestrians. The trend towards a more pedestrian friendly environment by

providing more space dedicated to this road user group is clearly visible even though trends are going

towards longer distances, which in turn are not accessible for pedestrians, for daily activities.

Table 10 Built up areas in the Netherlands, including pedestrian facilities (Methorst 2005: 10).

Although there are estimates of mobility developments on a European level as well as some data on

expected increase in infrastructures for certain VRU groups as presented above, there is no way to

present these developments for future comfort. As the model used for a quantitative representation of

comfort, based on mobility data and accident statistics, represents an approach only valid for countries

where no specific future trends are available, presenting comfort trends is not feasible. However com-

fort of vulnerable road users is a complex topic as already outlined above, mainly concerning subjec-

tive assessments of the immediate environment, including infrastructures and social interactions, as

well as environmental circumstances. As only very few studies provide a comprehensive model of

comfort, as proposed by the VRUITS project, which do not offer quantitative insight into this topic,

there is no actual data on comfort trends for different road user groups available.

The ECs mobility forecast as presented by Graham (2005) provide some insight into expected trav-

elled kilometres per road user groups and estimates for modal split, although only on a European lev-

el. However these expected developments can provide some insight into how comfort can be ex-

pected to change for VRUs depending on the four different scenarios of economic development.

D2.3


32

4. MARKET ANALYSIS

4.1 Introduction

The likelihood of applying the selected systems in 2020 and 2030 is analysed and the most appropri-

ate business model structures to increase the commercialization of these ITS are identified. Deploy-

ment issues of ITS for VRUs are discussed based on the analysis conducted.

4.2 Estimation on penetration rates: stakeholder consultation and market

assessment

This subtask aims at conducting a market analysis on the applications selected in task .2.3. For this

purpose information concerning the likelihood of applying these systems in 2020 and 2030 has been

collected through questionnaires sent to PPAA in charge of road infrastructure and manufacturers of

ITS.

4.2.1 Procedure

Design and distribution of questionnaires

In order to get information about the penetration rates, two types of questionnaires were developed,

one targeted to authorities, and the other one targeted to manufacturers of ITS (Appendix 1). Both of

them contained a brief description of the system and a small picture in order to make the question-

naire as friendly as possible. Each of us will be explained separately:

Manufacturers

Questionnaires designed for manufacturers contained questions on all relevant information for each

ITS considered. Aspects included are:

1. Estimation on how many users will have the system by 2020 and 2030, both in absolute numbers

and in percentage, and taking into account vehicles with OEM systems as well vehicles with retro-

fit/nomadic systems.

The kind of user depends on the system it is being considered: it can be pedestrians, cyclists, PTW´s,

passenger cars, goods vehicles, buses, or different combinations of these.

2. Main obstacles that must be overcome to achieve the deployment of the ITS

3. Success factors: what are the reasons why they think the ITS will be successfully introduced in their

country

4. Any additional comments regarding their institution´s deployment of the ITS.

Public Administrations

Questionnaires designed for PPAA contained questions on all relevant information for each ITS con-

sidered. Aspects included are:

1. Plans to invest in the system in the future

2. Consideration of investing in the system in the future

3. Consideration of co-financing or facilitating private investments in the system

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4. Estimation on how many systems there will be installed in their city by 2020 and 2030, both in abso-

lute numbers and in percentage.

5. How useful they think is the implementation of that service, and reasons for it

6. Main obstacles that must be overcome to achieve the deployment of the ITS

7. Success factors: what are the reasons why they think the ITS will be successfully introduced in their

country

8. Any additional comments regarding their institution´s deployment of the ITS.

Once the questionnaires had been designed, they were circulated around the partners involved in or-

der to make sure that all the information required for the subsequent CBA was compiled. After discus-

sion and several drafts, the final questionnaires were defined.

These were distributed to get the input from experts which are close to decision making on their view

on the implementation of the applications. The questionnaires were distributed through the VRUITS

contact list, Apart from distributing the questionnaires to the VRUITS project contacts, they were also

sent through the iMobility Forum VRU working group, ERTICO and the POLIS networks.

Response to the questionnaires

Unfortunately the response was smaller than expected. At the Second Interest Group Workshop, the

original questionnaires, which demanded estimates for the 23 systems selected for qualitative as-

sessment of D2.1, was reduced to the applications selected for quantitative assessment.

Only 8 questionnaires were received, 4 from the authorities and 4 from the manufacturers. Due to the

low responses the results have to be taken cautiously otherwise any conclusion could mislead to an

erroneous judgement.

Answers have been obtained from the following countries:

Authorities: Germany, Spain, Netherlands

Manufacturers: Germany, Austria, Finland, Nordic countries

Second Interest Group Workshop

The second Interest Group Workshop (IGW2) of the VRUITS project was held in Helsinki on

16.6.2014. The main purpose of the Second Interest Group workshop was to present the results of the

safety and mobility assessment and to select the applications for the second phase of the safety and

mobility assessment (Kruijf et. al., 2014). Table 11 shows the systems selected for quantitative as-

sessment at the Second Interest Group Workshop.

D2.3


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Table 11 ITS Systems selected for quantitative assessment in IGW2

B2V Bicycle-to-car communication

BSD Blind Spot Detection

CAL Crossing Adaptive Lighting

GWC Green Wave for Cyclists

INS Intersection Safety

IPTS Intelligent pedestrian traffic signal

IVB Information on Vacancy on Bicycle racks

PDS+EBR Pedestrian Detection System + Emergency Braking

PTW2V PTW oncoming vehicle information system

VBS VRU beacon system.

During the assessment process, the participants were requested to rate the applications both for their

impact on safety, mobility prioritise the applications, as well as on the easy on deployment and the

time to market.

Ease of deployment was scored from a minimum of 1 to a maximum of 5:

5 = very easy

4 = easy

3 = not easy, not hard

2 = hard

1 = very hard

Time to market was also scored on a scale from 1 to 5:

5 = on the market now

4 = on the market within 2 years

3 = on the market in 2020

2 = on the market in 2025

1 = on the market 2030+

The feedback received during IGW2 for the systems selected for quantitative assessment, is shown in Table 16 Results of the Second Interest Group Workshop: average of the results for the deployment related questions.

The results are integrated with the results of the questionnaire, as is described in Section 4.2.5.

4.2.2 Results of the questionnaires

Bicycle to car communication

The manufacturers perceive this system as more useful for bicycles than for cars. Only two manufac-

turers see it as useful for cars, considering that 50% of the new cars could have this system by 2030

and it could be installed in a maximum of 30% of the actual fleet. On the other hand, all respondents

consider it valid for bicycles, giving a range of market penetration between 10% and 30% by 2030.

The cost, data privacy, and technical complexities are the main obstacles. In addition, implementation

will take time because many people will think they do not need it.

D2.3


35

Implementation is seen as hard (2,15) by experts at the 2º IGW, but they consider that the system will

be on the market in 2020.

Blind Spot Detection

The manufacturers consider this system very useful because they estimate that it could be installed in

up to 100% of the passenger cars and goods vehicles by 2030. They state that manufacturers will

provide it if it is mandatory. The main obstacle could be that it is too expensive for goods vehicle own-

ers. The key factor will be if it is included as a regulation. Concerning technical obstacles they mention

reliable detection of VRUs all around the vehicle. They say that backover systems are being required

in U.S. and wonder about possible regulation in Europe if systems allow to reliably detect cyclists in

blind spots.

Implementation is seen as not easy, not hard by participants at the 2º IGW, and they give a score of 4.

46 for time to market

Crossing Adaptive Lighting (CAL)

The authorities do not show much interest in this system. They estimate that this system could be in-

stalled in maximum 10% of the intersections in their countries by 2030. As positive features they high-

light that it sounds simple, save electric costs, and increase the safety of pedestrians and cyclists.

However the main obstacle is that they perceive this system as not very cost-effective.

Experts at the IGW2 saw this system quite near the market though, giving it a score of 4.40. A lower

score was given to ease of deployment (3.40), meaning that they perceive it not easy not hard.

Green Wave for cyclists (GWC)

The administrations do not show much interest in this system. They consider that the system is useful

but very difficult to be implemented. It is useful because it reduces risks of accidents through lack of

hindrance at congested traffic signals. But it will have many obstacles to be implemented: political be-

cause it assumes a predominance of cyclists over motorized, and technical because the speed advice

cannot be adapted to different users and age groups (elderly cyclists) or distinguish between pedestri-

ans and cyclists.

The respondents do not perceive this system as very useful. The estimated range is 0-5% in 2020 and

0-30% in 2030. The main obstacles found are: difficult technical integration and coordination with other

traffic systems, possible conflict of interest with other road users, benefit versus cost will not seem jus-

tified except in some urban areas.

They point out that if this system is developed as mobile phone module or app then it could be more

effective.

The score of 3.69, given by participants at the IGW2, means that GWC will be on the market in 2

years, and its implementation is seen as not easy, not hard.

Information on vacancy on bicycle racks (IVB)

All of the authorities consider this system useful. They think that up to 50% of the cyclists in the city

and in the country will have the system by 2030. They perceive that this system offers an opportunity

of enhancing cycle mobility, but it will be limited to certain purposes of cycle use (shopping, tourists…).

The vision of the penetration rate for this system by the manufacturers is very different from the au-

thorities. They consider that only between 10% and 20% of the bicycles will have it by 2030. One of

the obstacles that they mention is that the bicycle racks are expensive in maintenance. Also, bicycle

D2.3


36

parking can be easily done without any high tech facility so the system should be combined with se-

cured parking of bicycles.

A score of 3.85 was given to this system at the IGW2. Thus they think that it will be on the market in

more or less 2 years. The implementation is seen as not easy, not hard.

Intelligent Pedestrian Traffic Signal (IPTS)

The responses of the administrations concerning this system vary significantly. From one administra-

tion that considers that the Intelligent Pedestrian Traffic Signal would be installed in 70% of the na-

tional intersections by 2020 and 80% of them by 2030 to other which does not see it useful. Authorities

reflect that somehow this system is useful, especially the optimization of times and the prioritization of

pedestrians over other road users as useful. They mention as success factors the easy implementa-

tion, potential cost reduction, and the fact that the pedestrian's interaction is not required.

Participants at IGW2 gave a score of 3.90 out of 5 on time to market for this system (Table 16), what

means that they think the system will be on the market more or less within 2 years. In addition, they

gave a poor score (2.70) on ease of deployment; thus they consider the deployment of IPTS hard.

Intersection Safety (INS)

Only two administrations consider that this system will be implemented in their country, in 2% and

10% of the intersections respectively in 2030. They see the system as a very technically complicated

one (broad equipment and very different types of intersections to be covered). It is also financially

complicated because it seems expensive. The system could be effective if the data is very accurate.

On the other hand, it could lead to a misuse of private data.

The answers from the manufacturers on the questionnaire are very diverse. The ranges of market

penetration go from 10%-80% for passenger cars in 2030, and 10%-100% for goods vehicles and

buses in 2030. For 75% of the respondents. the main obstacles are the cost of infrastructure and the

cost of the in-vehicle equipment. Thus. one of the respondents states that only if mandated will it get

high penetration.

Time to market for this system scored 3.00 at the IGW2, so in their opinion the system will be on the

market in 2020. Concerning ease of deployment, it is scored 2.40, so participants think that the de-

ployment of INS is hard. Therefore this opinion seems to support somehow the estimation of 2-10%

penetration rate in 2030 given by authorities.

Pedestrian Detection System + Emergency Braking

This system is perceived as very useful. The figures given by the respondents estimate a market pen-

etration of up to 50% passenger cars and goods vehicles by 2030 and 70% buses and coaches by

2030. The main obstacle observed is the detection of pedestrians in any weather condition. Concern-

ing economic obstacles, they mention that goods vehicle companies will not spend money on it.

The inclusion of pedestrian AEB systems into EURO NCAP rating system is seen as a success factor

for the penetration of this system.

Some questions raised by the respondents are:

- How to ensure that these systems are deployed in a harmonised way all over Europe.

- Have an eye on privacy issues. If at all necessary, the devices should be identified via the ve-

hicle-id. Pedestrian devices should not require personal identification at all. So every house-

hold member can use the same device.

D2.3


37

- Do these devices record every drive? Will there be an issue with evidence when accidents

happen?

The implementation of PDS+EBR is not seen as hard by participants at the 2º IGW, and they give a

score of 4.70 for time to market

PTW oncoming vehicle information system

The answers from the different manufacturers are very different. They think this system is more useful

for PTWs (15%-80% PTWs market penetration by 2030) than for passenger cars (10%-50% Passen-

ger cars market penetration by 2030).

The main perceived obstacles are: power consumption of the device, performance in poor weather

conditions, acceptance of the device by riders, the fact that drivers do not see PTW's as VRU, or the

cost of the device.

Implementation is seen as hard by the experts attending the 2º IGW, and they see the system in the

market within 5 years.

VRU Beacon System (VBS)

Only one administration shows interest in VRU Beacon system. This authority considers that this sys-

tem will be implemented in less than 1% of the pedestrian crossings in the upcoming years, both at

city as well as country level. There are many variables and possibilities that the information provided

to the driver may not be useful or correct in the 100% of the cases which means that the accuracy of

the data will be critical for this system to work. But they argue that if it succeeds it is the most accurate

way of communication between driver and VRU.

There is much variation on the answers from the manufacturers concerning this system. For new pas-

senger cars the market penetration range goes from 1%-5% in 2020 and 15%-80% in 2030, whereas

the retro fitment of passenger cars goes from 0%-5% in 2020 and from 10%-20% in 2030. The estima-

tion for pedestrians simple tags ranges from 0% to 30%, whereas if is used as cooperative system the

ranges go from 0% to 20% in 2030. For cyclists the estimation is higher: from 0% to 75% in the case

of simple tags, and from 0% to 50% if the system is cooperative. For PTWs the market penetration

estimated for this system varies from 2%-30% PTWs in 2020 and from 20%-90% PTWs 2030.

The participants at the IGW2, gave this system a score of 2.93 when evaluating time to market, so

according to their opinion the system will be on the market in 2020. However they think that the de-

ployment is hard.

The responses received from the authorities are shown in Table 12 and Table 13, from the manufac-

turers in Table 14 and Table 15.

Table 12 Main obstacles per system perceived by authorities

System Main Obstacles

Intelligent Pedestrian Traffic Signal Misuse of system by pedestrians

Intersection Safety Complicated system. Possible misuse of private data

Crossing Adaptive Lighting Not very cost-effective

VRU Beacon System Accuracy of the data

Information on vacancy on bicycle racks Bike parking is not considered as a problem by the bike user.

Green Wave for cyclists Very difficult to be implemented

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Table 13 Estimation by authorities of penetration rates of the systems selected by the years 2020 and 2030

SYSTEM

% Authorities interested

City Country

Range of penetration 2020




Intelligent Pedestrian Traffic Signal

100%

Minimum 0.50% 2% 1% 2%

Average 24.12% 40.50% 24.33% 34%

Maximum 90% 100% 70% 80%

Intersection Safety 50%

Minimum 0% 0% 0% 2%

Average 0.33% 3.33% 3% 6%

Maximum 1% 10% 5% 10%

Crossing Adaptive Lighting

75%

Minimum 0% 0% 0% 0%

Average 1% 6.70% 1% 6%

Maximum 2% 10% 1% 10%

VRU Beacon System 75%

Minimum 0% 0% 0% 0%

Average 0.50% 0.50% 1% %

Maximum 1% 1% 1% 1%

Information on va-cancy on bicycle

racks 100%

Minimum 1% 5% 5% 10%

Average 11.50% 21.25% 17.33% 21.33%

Maximum 30% 50% 30% 50%

Green Wave for cy-clists

25%

Minimum 0% 0% 0% 0%

Average 0.33% 0.33% 0.50% 0.50%

Maximum 1% 1% 1% 1%

Table 14 Main obstacles found by manufacturers

System Main obstacles

Bicycle to car communica-

tion

Technically complex. Performance of the device (visibility of warnings.…) in poor

weather conditions and in strong lighting. Power consumption of the device. Many

people will think they do not need it.

Intersection Safety Cost of infrastructure and in-vehicle equipment. Only if mandated will it get high

penetration

VRU Beacon System Not sure if people want to carry such a device all time. Cost of the device for the

individual

Information on vacancy on

bicycle racks

Bike parking is not considered as a problem by the bike user. Cost of the complete

system: should be combined with secured parking of bicycles

Green Wave for cyclists Cost of the equipment for bicycles (cooperative version). Technical integration with

traffic management system. Conflict of interest with other road users

PTW oncoming vehicle

information system

Power consumption of the device. Performance in poor weather conditions. Ac-

ceptance of the device by riders. Drivers do not see PTW's as VRU. Cost of the

device. Needs to be implemented by regulation like eCall

Blind Spot Detection Reliable detection of VRUs all around the vehicle. Cost of the device; two expen-

sive for goods vehicles owners.

Pedestrian Detection Sys-

tem + Emergency Braking

Reliable detection of pedestrians in all weather conditions. Goods vehicle compa-

nies will not spend money on such topics

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Table 15 Estimation by manufacturers of penetration rates of the systems selected for the years 2020 and 2030.

SYSTEM

Passenger Car

Passenger car retrofit

Pedestrian (simple)

Pedestrian (cooperative)

Bicycle (simple)

Bicycle (cooperative)

PTW Goods vehicle

Goods ve-hicle retro-

fit Bus Bus retrofit

2020 2030 2020 2030 2020 2030 2020 2030 2020 2030 2020 2030 2020 2030 2020 2030 2020 2030 2020 2030 2020 2030


Minimum 0 0 0 0 1 10 - - - - -

Average 5.3 15 1.3 10 3 19

Maximum 20 50 5 30 5 30

Intersection Safety

Minimum 1 10 0 0 - 0 10 0 0 0 10 0 0

Average 3 33 3.8 10 4.5 40 7.5 35 6.5 45 2 36

Maximum 5 80 10 20 10 100 25 100 20 100 5 100

VRU Beacon System

Minimum 1 15 0 10 0 0 0 0 0 0 0 0 2 20

Average 2.5 36 2.3 16 2.5 7.5 2.8 14 5 19 14 25 14 48

Maximum 5 80 5 20 10 30 5 20 20 75 50 50 30 90


bicycle racks

Minimum - - - - 0 10 - - - - - - - - - -

Average 1.8 16

Maximum 5 20

Green Wave for cyclists

Minimum - - - - 0 0 - - - - - - - - - -

Average 2 13

Maximum 5 30

PTW oncoming vehicle infor-

mation system

Minimum 1 10 - - - 1 15 - - - - - - - -

Average 2 27 4 36

Maximum 5 50 10 80


Minimum 1 15 0 0 - - 3 30 0 0 3 30 0 0

Average 10 41 2.8 11 20 58 11 40 21 58 10 40

Maximum 30 100 5 30 50 100 20 100 50 100 20 100


tem + Emer-gency Braking

Minimum 0 5 - - - - 0 0 0 5 -

Average 3 29 7.8 29 8 35

Maximum 10 50 20 50 30 70

D2.3


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4.2.3 Second Interest Group Workshop

During the assessment process of the qualitative assessment of the ITS systems on the IGW2 in Hel-

sinki, the participants were requested to rate also the ease of deployment and the time to market of

the systems.

Table 16 shows the average quantitative results for these deployment aspects, for the ITS applications

which were selected for quantitative assessment.

Table 16 Results of the Second Interest Group Workshop: average of the results for the deploy-ment related questions.

System Ease of deployment Time to Market

Bicycle to Car communication 2.15 3.00

Blind Spot Detection 3.31 4.46

Crossing Adaptive Lighting 3.40 4.40

Green Wave for Cyclistso 2.69 3.69

Intersection Safety 2.40 3.00

Intelligent Pedestrian Traffic Signal 2.70 3.90

Information on vacancy of bicycle rack 3.31 3.85

Pedestrian Detection System/ Emergency Braking 3.50 4.70

PTW oncoming vehicle information system 2.64 3.50

VRU Beacon system 2.40 2.93

4.2.4 Combination of the questionnaire and IGW scenarios

The scenarios have been developed based on the input of the questionnaires and the input at the

second Interest Group Workshop. The questionnaire attempted to get all the information required for

the impact assessment, resulting in a task, which was too challenging for many candidate respondees.

In order to get feedback on the scenarios developed, a simpler questionnaire would be needed. For

this questionnaire, the number of questions will be limited to 1-2 per system. As most important num-

ber the penetration rate at 2030 is selected.

A description of the intended implementation rate for 2030 has been conducted (Table 17) merging

the data gathered through questionnaires, and through the IGW2.

For both questions answered at the IGW (year to market and ease of implementation) a parabolic

conversion has been used to convert the year of market introduction and the possible penetration rate.

It was assumed that very easy would mean 100% penetration, very hard 1% penetration, and hard

10% (the other are then about 30% for not hard-not easy and 60% for easy).

An average of the values of the questionnaire and the IGW feedback was then calculated for the

penetration rate of 2030. This value was possibly adapted taking the remarks on the questionnaires

and the feedback in the IGW into account. In addition, the consistency of the penetration rates for

function using identical equipment was checked, more specifically the penetration rates of C-ITS

equipment in vehicles (INS, VBS, PTW2V, B2V), for cyclists (VBS, GWC, B2V), for PTWs (VBS,

PTW2V). Penetration rates for bidirectional equipment (B2V, GWC, PTW2V) should be lower than for

unidirectional equipment (VBS).

D2.3


41

Table 17 Scenarios, obtained from combining questionnaire results with feedback from IGW2.

System Infrastructure penetration rate Users´ penetration rate

B2V 10% of bicycles; 40% of vehicles equipped with C-ITS

equipment supporting B2V functionality

BSD 44% of vehicles equipped

CAL 18% of major pedestrian crossings in

urban areas

GWC 1% of major intersections in urban

areas

10% of bicycles equipped

INS 5% of signalised intersections in urban

areas

40% of vehicles equipped with C-ITS equipment supporting

INS functionality

IPTS 32% of signalised intersections in ur-

ban areas

IVB 25% of bicycles equipped

PDS+EBR 36% of vehicles equipped

PTW2V 28% of PTWs equipped; 40% of vehicles equipped with C-

ITS equipment supporting PTW2V functionality

VBS 1% of major pedestrian crossings in

major cities

5% of pedestrians, 15% of cyclists;40% of PTWs equipped ;

40% of vehicles equipped (with C-ITS supporting equipment)

4.2.5 Translation of penetration rates to absolute numbers

For the impact assessment, the total amount of equipped vehicles, VRUs and equipped infrastructure

is desired.

The vehicle park in EU-28 consists of more than 240 million passenger cars. 32 million of PTW and

Lorries. and 1 million buses and coaches (Appendix B. ). So, even if the market penetration of a sys-

tem is low. the potential market is still very big. In 2013,. almost 12 millions of passenger cars and

more than 1.1 million of Power Two Wheelers were newly registered. Around 13.7 million units of ve-

hicles were newly registered in EU-27.

To estimate the number of potential vehicles which will have an in-vehicle system a projection of new

registrations of each vehicle category was used (a five years projection of the new registrations was

used for the year 2020. and 15 years of new registration projections was used for 2030). Whereas to

estimate the number of vehicles which will retro-install the system what has been taken is the park

vehicles in Europe-28 in 2013. However, these estimations and extrapolations have to be taken cau-

tiously because have been done with estimations on penetration rates from a very few number of an-

swers.

The total number of bicycles in which these two systems could be implemented has been estimated

considering the bicycle sales in Europe in 2012 (Appendix B.4).

To estimate the number of potential pedestrians which will have the system the whole European popu-

lation has been considered.

The estimated penetration rates have been applied to these estimations. This data has been summa-

rized in the following paragraphs, and can be seen in Table 18.

The four systems assessed by the authorities are related to a certain type of location: either intersec-

tions or zebra crossings. Only one city has provided its data of the total number of intersections and

zebra crossings. As a consequence, an estimate for EU-27 cannot be provided.

D2.3


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Table 18 Estimation by amount of equipped vehicles (in Millions of units) and VRUs for the ITS systems selected in 2020 and 2030 in EU-27.

SYSTEM

Passenger Car

Passenger car retrofit

Pedestrian (simple)

Pedestrian (cooperative)

Bicycle (sim-ple)

Bicycle (co-operative)

PTW Goods vehicle Goods vehicle

retrofit Bus Bus retrofit

% Amount % Amount % Amount % Amount % Amount % Amount % Amount % Amount % Amount % Amount % Amount


2020 2 1,292 1,3 3,144 3 2,951

2030 20 38,752 5 12,091 10 29,510

Intersection Safety

2020 3 1,938 3,8 9,189 4,5 0,378 7,5 2,415 6,5 0,012 2 0,018

2030 40 77,505 10 24,182 40 3,357 25 8,050 40 0,217 5 0,045

VRU Beacon System

2020 2,5 1,615 2,3 5,562 1 5,066 1 5,066 5 4,918 1 0,984 5 0,323

2030 40 77,505 5 12,091 5 25,331 5 25,331 20 59,019 15 44,264 40 7,763


bicycle racks

2020 1,8 1,771

2030 25 73,774

Green Wave for cyclists

2020 2 1,967

2030 - 15 44,264 - - - -

PTW oncoming vehicle infor-

mation system

2020 2 1,292 4 0,259

2030 40 77,505 28 5,434


2020 10 6,459 2,8 6,771 20 1,678 11 3,542 21 0,038 10 0,090

2030 44 85,255 5 12,091 50 4,196 20 6,440 50 0,271 20 0,179


tem + Emer-gency Braking

2020 3 1,938 7,8 0,655 8 0,014

2030 36 69,754 36 3,021 36 0,195

Total Amount in EU-27

2020 100 64,587 241,825 506,624 506,624 98,365 98,365 6,469 8,392 32,200 0,181 0,896

2030 100 193,762 241,825 506,624 506,624 295,095 295,095 19,407 8,392 32,200 0,542 0,896

43

4.3 Potential business models

4.3.1 What are business models

A business model for ITS describes the way business/government expects to recover costs of imple-

menting ITS technology when providing services for a longer period of time. It describes the prod-

ucts/services that will be provided, the funding, the relationship between different stakeholders and the

mechanism by which business opportunities will be exploited.

Although ITS is associated with modern technologies the business models used originate from the first

generation innovation models; technology push models. In this model innovation in technology is lead-

ing in research and development. Although there have been advancements in engineering and manu-

facturing. the marketing and commercialization of the technology is lacking. According to Giannoutakis

Li (2012) the marketing/commercialization is the most crucial aspect of capitalizing on the technologi-

cal innovation at the firm level. This section aims to identify and suggest the most relevant and suita-

ble business model structures to increase the commercialization of the most promising and close-to-

market ITS systems that are prioritized and assessed by VRUITS. Business models for four types ITS

are discussed: Cooperative ITS, In-vehicle ITS, Cyclists ITS and Public ITS.

The 2DECIDE project defines the following reference business models for ITS (Kulmala, 2012):

1. Subscription Model (paid service through periodic fees) Revenue is raised through

periodic (weekly, monthly and annual) fees. This is a popular model for supplying access

to a service that is frequently used. The advantage for the service provider is that revenue

is raised in advance and thus providing more certainty of regular income. The advantage

for the user is that costs of using the service are known in advance and access is unlim-

ited within the subscription limit.

2. Usage Model (paid service – pay per use) Revenue is raised through actual usage of a

service (pay-per-use). Usage may be measured in time, per bytes, per area or per ses-

sion. Thus, if you don’t use the service - you don’t pay for it. The provider earns money by

applying a mark-up to the actual cost of each item or service.

3. Free Model (free service – offered by authorities / socio-economic benefits generat-

ed) There is no direct revenue raised through this model, although there will be indirect

benefits. Public sector organisations often employ this model. The immediate benefits are

intangible, e.g. a betterinformed citizen or better policy effectiveness, or the benefits may

be financial in the long term, e.g. less congestion, emissions, accidents etc.

4. Advertising Model (free service – revenue generated via for instance advertisement)

This business model creates a community of users bound together by a common purpose

or viewpoint. Revenue can be based on the sale of other services. Facebook, Twitter and

other social networking websites use the community model to create revenues from ban-

ner advertisements and sales of branded merchandise.

5. Enticement Model (free service – revenue generated via additional services) Here,

part of the service is provided free of charge as a lure to entice the user. Revenue is

raised from the sale of other products and services. This is often used for information and

web-based services. No direct or immediate services are thus created, unless combined

with another model.

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4.3.2 Business Model for Cooperative ITS

4 of the 10 ITS selected for this study can be labelled as cooperative ITS. Cooperative ITS refers to a

system in which two or more of: people, vehicles, nomadic devices and infrastructure are connected

and cooperate by sharing information (Nilsson et al. 2012).

Cooperative ITS services are still in the development phase and are not widely used. The focus in

studies on cooperative ITS is on standardization of the communication between people, vehicles, no-

madic devices and infrastructure and on other technical issues. There is still a lack of knowledge on

how cooperative ITS can be commercialized.

Products/services

The four cooperative ITS will be shortly described in the upcoming part. Topics that will be discussed

are the technical characteristics, main beneficiaries and current state of affairs.

Intersection Safety (INS)

INS uses C-ITS technology to inform drivers and, optionally, VRUs approaching an intersection about

the state of the activities at the intersection. In-vehicle and infrastructure based C-ITS technologies

enable communication between vehicles and roadside units. The system can provide left- and right-

turning assistance for vehicle users. The Road Side Unit can detect VRUs and communicate this to

vehicles that are turning right or left into the path of a VRU. The driver will be warned or, optionally, the

vehicle will automatically brake in case of a dangerous situation. VRUs can be informed of a danger-

ous situation by flashing lights or sound signals. Besides turning assistance, the system can also iden-

tify situations in which a vehicle drives perpendicular to the path of a VRU. An INS is a rather complex

system that is still under development. Participants of the Second Interest Group Workshop indicated

that if the system becomes operational the potential safety benefits are significant.

VRU Beacon System (VBS)

A VBS makes use of a tag or a device held by a VRU that can be detected by a device in vehicles or

in the infrastructure. The system calculates the trajectories of the VRU in relation with the trajectories

of the vehicle. In case of a chance of collision the driver will be warned.

Either a specific device or a smartphone with an application can be used by the VRU to transmit C-

ITS( cooperative traffic compliant) messages. In particular at night and during adverse weather condi-

tions cyclists and pedestrians make up for most of the traffic accidents. The VBS has the potential to

significantly decrease the number of accidents with VRU by increasing their visibility.

Bicycle to car communication (B2V)

B2V informs vehicle driver about the presence and potential collisions with bicycles. Cyclists are in-

formed on their mobile phone about oncoming vehicles and potential collisions. The vehicle and bi-

cycle needs a C-ITS unit to send and receive messages with bicyclists. The C-ITS unit is also used for

the VBS.

PTW oncoming vehicle information system (PTW2V)

This system addresses the problem of visibility and awareness of motorcycles by enabling communi-

cation between vehicles and PTWs. Vehicle drivers and MC are informed about each other’s location.

Vehicles and PTWs can communicate using a standard C-ITS device which is also used for VBS and

B2V.

45

Funding

For the development of a cooperative ITS, investments from and collaboration from multiple actors are

needed, from both in-vehicle manufacturers, infrastructure providers and third parties, providing devic-

es and applications for VRUs. The European mandate M/453 urged the standardisation organisations

ETSI and CEN to developed the minimum set of standards determining the interoperability of C-ITS. In

order to overcome the lack of coordination between the different actors and to develop a joint strategy

for deployment, the Amsterdam Group, a cooperation between both automotive sector companies and

road operators/authorities, was set up. (Amsterdam Group, 2013).

C-ITS are based on devices in vehicles which communicate using standardised protocols and mes-

sage sets. The C-ITS devices can be either installed in the vehicles (either pre-installed or retrofitted),

or be nomadic. For the VRU device, the device can either be a dedicated device with all functionali-

ties, be an add-on device to a smartphone, or be implemented as a smartphone app.

For the in-vehicle devices and the dedicated devices, the cost of the service is included in the price of

the device.

For the smartphone app, the Subscription Model and Free Model can be viable business models. De-

velopers can create applications based on this technology which enables communication between

VRUs, infrastructure and Vehicle drivers. Following the Subscription Model people will be able to use

the application based on a fixed periodical fee. As the potential application will have socio-economic

benefits, public organizations may be willing to finance the development and make it free of charge

(Free Model).

Business opportunities

Cooperative ITS technology

The amount of vehicles that are equipped with cooperative ITS technology is currently very low. ITS-

G5 equipment will be installed in cars as standard equipment from 2015 onwards. IEEE 802.11p

chips, which can be embedded into phones, are expected to be introduced in the market in 2014. The

following figure shows the expected worldwide OEM V2V attach rate, as predicted by IHS (2014) and

Frost (2014).

Figure 30 Worldwide OEM V2V attach rate

Figure 31 shows the historical road map for IEEE 802.11p equipment (NXP. 2014).

46

Figure 31 Road map for IEEE 802.11p equipment

The Amsterdam group has provided guidelines for the implementation of C-ITS applications. Deploy-

ment of cooperative ITS will follow a phased approach starting in 2015 with not too complex devices

and a set of “Day 1” applications offering early user-benefits already at low penetration rates (Amster-

dam Group, 2013). The next deployment and migration phase might be initiated after 3 to 7 years de-

pending on the innovation and lifecycles of vehicles and infrastructure components. With increasing

penetration rates, further cooperative use cases / applications become feasible and further stakehold-

ers might be involved. (Amsterdam Group, 2013)

Retrofit and aftermarket devices will be able to support the development and penetration increase of

C- ITS (Amsterdam Group, 2013), especially for services without stringent latency requirements.

Regarding the use of C-ITS for VRUs and on VRU vehicles, possibilities areas mentioned above – a completely dedicated device, an add-on device to a smartphone or a smartphone app.

Smartphones could also be used – in possible combination with add-on devices for e.g. ITS-G5 com-

munication –to gather data and for service consumption (Nilsson et al. 2012). A drawback from using

smartphones for both actions is that the type of cooperative ITS services that can be developed are

limited to the technical capabilities of smartphones. A benefit from using smartphones is that they

have a high market penetration which enables a fast deployment of the technology.

Barriers

Multiple and competing actors have to invest in a common cooperative system. Results from a stake-

holder consultation in Sweden indicate that hesitation based on short-term business reasoning is an

important barrier that may prevent the creation of a cooperative ITS (Nilsson et al. 2012). To create a

cooperative ITS a group of organization is needed that take a leading role and are willing to invest in

their mutual relations.

The Amsterdam Group’s main aim is to improve collaboration between the stakeholders for the de-

ployment of Day 1 C-ITS services. Also the European Commission has decided to take a more promi-

nent role in the deployment of cooperative systems, and set up the “C-ITS Deployment Platform” (Eu-

ropean Commission, 2014), which will address the main barriers and enablers identified for the de-

ployment of C-ITS in the EU, in relation to the services likely to be introduce in the first stage (Day 1

applications) in view to provide policy recommendations to the European Commission for the devel-

opment of a Communication on the Deployment of C-ITS in the EU by the end of 2015.

In addition to the investments in road side infrastructure, cities need to invest the integration of C-ITS

services like traffic data collection, traffic data analysis, traffic control and traffic management. Risks

47

for achieving the intended benefits may arise from uncoordinated development and standardisation,

but also from proprietary deployment of cooperative ITS hard- and software for vehicles and coopera-

tive infrastructure. Other risks might arise from insufficient public budgets on national, county and city

level for financing investments, maintenance and continuous operation of C-ITS as well as research

and development activities for enhancement of new services (Proskawetz, 2013)

The services addressed in this report require also the involvement of parties, who develop devices

and applications for VRUs.

A report by the Environmental Protection Agency (2010) indicates that it takes between 15 to 20 years

before vehicle technology reaches maximum market penetration. A critical mass of people making use

of cooperative ITS is needed to create a viable business model. People who decide to buy a new ve-

hicle with cooperative ITS technology will not directly experience the benefits but will face the addi-

tional costs. The lag between the technical possibilities and realization is an important barrier that pre-

vents the deployment of communication systems between cars, PTW, bicycles and pedestrians which

are part of ITS analysed in this study. For vehicle manufacturers the production processes of new

technology are costly and soon become obsolete due to technological innovation. With a lag of 15 to

20 years before the technology reaches maximum market penetration this is a serious barrier for

manufacturers to invest in cooperative ITS technology

4.3.3 Business Model In-vehicle ITS technology

ITS like ‘’Blind Spot Detection’’ and ‘’Pedestrian Detection System’’ which are part of the 10 ITS which

are evaluated in this study are in-vehicle technologies that decrease the change of vehicle collision

with PTW, bicycles and pedestrians. VRUs benefit significantly from both technologies. Although

VRUs are the main beneficiaries of both technologies it is up to vehicle users to decide whether to

purchase vehicles equipped with in-vehicle ITS technology.

Products/services

The two in-vehicle ITS will be shortly described in the upcoming part. Topics that will be discussed are

the technical characteristics. main beneficiaries and current state of affairs.

Blind Spot Detection (BSD)

A BSD system uses vehicle sensor technology to detect pedestrians, bicyclists and PTW riders in

blind spots around the vehicle. After the detection of VRUs or other objects in the blind spot of the ve-

hicle the system provides a warning to the driver. The system is in particular interesting for large vehi-

cles like trucks and buses. The main beneficiaries of the system are cyclists and PTW riders.

Pedestrian Detection System (PDS) + Emergency Braking.

This in-vehicle system continuously scans for VRUs in its surrounding to detect a possible collision.

The system uses cameras, radar and infrared sensors to detect living objects in the car’s path of trav-

el. When the system detects a possible collision it will warn the driver of the vehicle through either

sound, visual signals or vibration of the steering wheel. The system works at all speed levels but is

most effective at lower speeds. Besides warning, the system can in case a driver fails to respond in

time, intervene through braking. At low speeds the system is intended to prevent a collision, at higher

speeds the system should reduce the impact of the crash.

As such, PDS+EBR (also called Pedestrian Collision Mitigation Systems) is a second generation of

Automatic Emergency Braking, and basicly uses the same sensors. Pedestrians and cyclists are much

more difficult to detect and identify than vehicles, since they have a much smaller footprint. PDS are

already available as additional options in certain vehicles. Car manufacturers like Volvo, Daimler, Audi

48

and BMW are using PDS systems (some with emergency braking) for a couple of years now. Besides

pedestrians the latest systems are able to detect cyclists as well. The first cyclists´ detection system

was introduced in 2013 by Volvo.

The earlier described VRU beacon system can enhance the effectiveness of the PDS+EBR as these

systems currently cannot detect road users outside the sight of the vehicle sensors. When the market

penetration of PDS+EBR will increase this may help to increase the demand of VBS.

Funding

The development of in-vehicle ITS will most probably be funded by the customers of vehicle manufac-

tures that pay for the technologies. As both ITS will have positive effects on traffic safety and comfort

for multiple traffic participants, it is likely that public organizations and insurance companies are willing

compensate the vehicle users. This will be further examined in the next paragraph. The reference

business models described do not relate to this type of ITS.

Insurance incentives

Vehicle users will prefer better road safety to prevent injuries to themselves and damage to others on

the road. Although they value higher road safety, they may be reluctant to pay for the new technolo-

gies. Vehicle users need to bear the costs for the technologies whereas especially VRU benefit from

better road safety. To create demand for these new technologies among vehicle users, financial incen-

tives can be an interesting method.

The costs of road crashes for vehicle users are limited to direct costs and compensation. These costs

can include compensation for families for loss of income and, in the case of serious injury, costs of

rehabilitation and care. Vehicle users pay for these costs via mandatory insurance premiums or

through social insurance schemes.

Insurance companies have to a certain degree the possibility to differentiate their premiums. Dis-

counts on insurance premiums based on driving history are common. The fewer accidents caused in

previous years the lower the premium. Providing discounts for vehicle users who have a car with ’Blind

Spot Detection’’ and/or ‘’Pedestrian Detection System’’ can be a way to compensate for the additional

costs associated with these technologies. When these technologies will cause a significant decrease

in traffic accidents, insurance companies may be willing to introduce discounts.

ITS can be a basis for further differentiation of insurance premiums. The information generated by the

systems can be used by insurance companies to provide incentives based on current driving behav-

iour (Pay How You Drive). There are different examples of insurance companies that already make

use of current driving behaviour to differentiate their insurance premiums (Tooth, 2012).

The deductions based on actual driving behaviour may become part of a business model for the de-

velopment of ITS. However regulation in certain EU member states may limit the possibilities for cost

reflective pricing of individual risks. When insurance premium deductions are used to increase invest-

ments in vehicle technology for ITS, regulations need to be adapted to increase possibilities for cost

reflective pricing of individual risks.

Public incentives

Like the incentives that can be provided by insurance companies, the government may also offer in-

centives for investments in technologies that increase road safety. A benefit of insurers in relation to

the government is that they have to compete and will therefore innovate to find the best way to influ-

ence the decisions of vehicle users. In case of behaviour depended incentives privacy concerns may

prevent government from collecting the information.

49


Safety as a selling point

Safety has become a factor which enables vehicle manufactures to differentiate themselves from

competitors. Different studies show that people value road safety. A study by Andersson (2005) shows

that people value preventing a fatality to 1,2 million euros. Besides a general willingness to prevent

road accidents, vehicle users face legal liability in case of a collision with VRUs.

In most EU member states the law will find a vehicle driver culpable after accidents between vehicles

and VRUs. In the Netherlands and Germany even strict liability rules apply. This means that anyone

who uses a vehicle that might become a dangerous object in a collision will be liable for any damage

that arises from the use of the vehicle (lcc, 2009). Vehicle users that are aware of their legal liability

will be interested in technologies that reduce the change of accidents with VRUs. The legal liability of

vehicle users and the general willingness to reduce road accidents can create incentives for vehicle

manufactures to develop safer cars and invest in technologies like ’Blind Spot Detection’’ and/or a

‘’Pedestrian Detection System’’.

A way to indicate the safety of vehicles is by using a safety score. The safety score of vehicles is be-

coming more important for vehicle owners. One important safety score is developed by the European

New Car Assessment Programme (EuroNCAP). This is a programme for testing and rating the safety

performance of new vehicles. It is an independent programme and has no commercial interest in the

vehicle manufacturers. Vehicle users are aware of the programme and the EuroNCAP score is used in

the competition between vehicle manufacters (Elvik, 2010). In-vehicle ITS technology will increase the

EuroNCAP score and may thereby increase the attractiveness and commercial value of the vehicle.

EuroNCAP addresses currently AEB (Automatic Emergency Braking) and BSD for collision between

vehicles, and plans to include pedestrian testing for AEB in 2016 (EuroNCAP, 2014). Using the safety

concept as a selling point is also applicable to business models for cooperative ITS systems which

require specific in-vehicle technology.

Barriers

The in-vehicle and cooperative ITS will increase the cost of the vehicles. As a consequence vehicle

drivers may not be willing to purchase the additional technologies as long as they are not mandatory.

The amount of information that will be shown on the HMI of PTW drivers and VRUs is also likely to

increase, and if the systems cause too much false or nuisance warnings, driver may also prefer to

switch off the applications.

The different systems also have unintended events. The VRUITS safety assessment addresses the

unintended effects and their impact on safety and mobility. Negative unintended effects, like more

risky behaviour, may cause insurance companies and public organisations to be reluctant to invest or

provide incentives. Understanding the possible adaptations in driving behaviour is crucial to convince

insurance companies and public organisations to invest.

4.3.4 Business Model Public ITS

The development of 2 of the 10 selected ITS, ‘’Intelligent Pedestrian Traffic Signal’’ and ‘’Crossing

Adaptive Lightning’’ will most probably rely on public funding. The European Union and the national

and local governments are the primary source of funding for ITS infrastructure technology.

Products/services

The two ITS that will most probably rely on public funding will be shortly described. Topics that will be

discussed are the technical characteristics. main beneficiaries and current state of affairs.

50

Crossing Adaptive Lighting (CAL)

CAL is a system installed at zebra crossings that lights the zebra crossing when pedestrians or cy-

clists use it. Via an automated device the pedestrian or cyclist is detected and the lights are activated

or brightened. The system increases road safety by raising the visibility of pedestrians/cyclist to vehi-

cle users. A study by Hakkert et al. (2002) showed the impact of the system. The rate of vehicles giv-

ing way to pedestrians doubled. a reduction in the share of pedestrians crossing outside the crosswalk

area up to 10% and a significant reduction in vehicle-pedestrian conflicts to a rate of <1%. The sys-

tem is not of interest for zebra crossings that are constantly used by pedestrians/cyclist. This will result

in lights that are constantly flashing lowering the effectivity.

Intelligent Pedestrian Traffic Signal (IPTS)

IPTS is a traffic signal control system that uses sensors such as an infra-red camera to determine the

presence of pedestrians and adjusts the traffic signals accordingly. The system will lower accidents

between vehicles and pedestrians at signalized intersections where there is a zebra crossing.

Funding

From the reference business models, the Free Model is the most suitable model for the two Public ITS

earlier described. The Free Model is a model often employed by public organizations. In this model a

free service is provided where no direct revenue will be raised for the development of the ITS. The

growing austerity at both the national and local level in member states of the EU set barriers to wide-

spread use of the Free Model for the funding of ITS.


The benefits of ITS should be communicated to the public and decision-makers to raise support for

solutions that that improve travel safety, comfort and efficiency. The public can be of vital importance

to motivate the decision-makers at the governmental level to finance ITS related equipment. Good

communications to decision-makers would be aided by cost-benefit analyses comparing the new

technology with current practices.

An article by Deakin, Fric and Skabardonis (2009) states that elected official and agency leaders who

take decisions whether to invest in new technology, complain about the jargon that technology devel-

opers often use. Policy makers like to have a clear description of the benefits of new technology and

are interested in the outcomes it will generate and what it will cost compared to other ways of achiev-

ing the same.

Barriers

In the IPTS system pedestrians have priority over vehicle users. When pedestrians decide to cross an

intersection the traffic signals will be adjusted. ITS systems may also have negative unintended ef-

fects, which may possibly involve an increase of pedestrians crossing during the red phase, and an

increase of the waiting time for vehicles, and hence possibly increase road congestion in cities. Public

organizations may be reluctant to invest in ITS systems which have a negative impact on vehicle us-

ers.

4.3.5 Business Model Cyclists Applications

2 of the 10 selected ITS, “Information on Vacancy on Bicycle racks” and ‘Green Wave for cyclists’’ are fo-

cused on cyclists and involve the development of a smartphone application.

51

Products/services

The two ITS will be shortly described. Topics that will be discussed are the technical characteristics,

main beneficiaries and current state of affairs.

Information on Vacancy on Bicycle racks (IVB)

The system provides information via a free phone app on the number and closest available bicycle

racks. The bicycle racks may be equipped with an integrated locking system for the bike. Currently

there are applications available (for example in Seattle) that allow users to locate a nearby bicycle

rack. However there are currently no systems that are using bicycle racks with an integrated locking

system and which are able to indicate whether the bicycle racks are vacant.

Green Wave for cyclists (GWC)

A personal device (a smart-phone or a bicycle computer) provides a speed advice to cyclists. If they

follow the advice they are guaranteed a green light at the next controlled intersection. The personal

device needs to determine the location of the cyclist to provide the speed advice. The system is easi-

est to implement in case of a fixed time traffic light controller. There are possibilities supporting adap-

tive time traffic light controllers as well.

Funding

To develop a “Green Wave for cyclists” system, infrastructure providers need to publish the data of the

fixed time traffic light controllers. Based on this data, developers can create an application for either a

smartphone or bicycle computer that provides cyclists with speed advice that will grant them a green

wave at the next intersection. Different reference business models can be of interest for the develop-

ment of the application.

Using the subscription model, cyclists pay a periodic fee to the application developers, which enable

them to make use of the system. The periodic fee can decrease as more cyclists make use of the ap-

plication. This as the marginal costs of additional users will be almost nil. An alternative to the sub-

scription model is the advertisement model, where the application comes free of charge. As the group

that makes use of the application is delimited they can be valuable for companies that have cyclists as

their customer base. The advertisements that will reach the delimited group will finance the develop-

ment of the application.

To finance the bicycle racks system different business models can be used. Systems that show re-

semblance to the bicycle racks system with locking system are the bike rental services like Velib (Par-

is) and Citi Bike (New York). These services party use a Usage Model and an Advertisement Model.

To make use of the bicycles people pay a fee based on time. The advertisement income is generated

by showing ads on bicycles and by companies that link their name to the program.

In a similar fashion to the bike rental programs but with privately owned bicycles, cyclists will pay to

securely park their bicycles in bicycle racks with an integrated locking system. To generate advertise-

ment money companies can link their name to the service. The user fees and advertisement money

will be used to install bicycle racks with an integrated locking system and to develop a free application

that informs people on the number and closest available vacant bicycle racks. A subscription model

can provide cyclists with unlimited use of the bicycle racks for a fixed periodic fee.


To make travelling by bike an alternative to other travel options the relative amount of travel time is an

important factor. Both ITS applications help to reduce the relative travel time. The bicycle racks appli-

52

cation reduces the time needed to find a vacant parking spot for your bike. The application will show

the best options and by using navigation the vacant parking spot is easy to find. The Green Wave ap-

plication will reduce travel time by bike because waiting times at intersections will be lower. A study by

Börjesson and Eliasson (2012) showed that cyclists’ value of travel time savings turns out to be high

considerably higher than the value of time saving on alternative modes. The time savings achieved by

both systems may therefore be a strong selling point.

Bike theft is a big problem in most cities. Bicycle theft is a crime that is largely unchallenged by the

police and is frequently not reported (Sidebottom Thorpe 2009). Cyclists are more than four times as

likely to be victims of vehicle theft than are car owners (van Dijk, 2007). The bicycle theft problem

opens a market for solutions that reduce the chance bikes get stolen. The bicycle racks system is

such a solution as it makes people aware of the presence of safe parking spots and provides a safe

way to store their bike.

Most city councils have the ambition to increase the use of bicycles in their city. Bicycle theft is the

highest per bicycle owner in cities where bicycles are a popular way of transport (van Dijk, 2007). The

chance your bike gets stolen increases the more popular is cycling in the city you are living. Therefore.

city councils that aim to increase the share of bicycle travel in their cities need to address the problem

of bicycle theft to make their ambition become reality. The bicycle racks system may be an interesting

solution for city councils to cope with the problem of bicycle theft in their cities.

Barriers

A study in Montreal, Canada showed that only 37 percent of the cyclists are willing to pay for better

parking (Van Lierop et al., ). Two in five people that were not willing to pay for parking cited cost, while

one in five did not want to pay on principle. Only 30 percent were willing to pay a dollar for parking.

This reluctance to pay for bicycle parking may be a significant barrier for the development.

4.4 Road map for ITS deployment

This section discusses deployment aspects of ITS in general, and ITS for VRU in particular. It will start

with a general discussion on deployment. This is largely based on the results of the SAFESPOT pro-

ject, which performed an in-depth analysis of deployment issues for cooperative safety-oriented ITS

for cars, and is therefore one of the lead examples of a recent deployment analysis. It then discusses

deployment issues of ITS for VRU based on an analysis of the questionnaire results.

Deployment

Deployment makes the difference between a potential impact of an ITS and a realized impact. History

shows that this involves more than a technical realization of the system. For example, ACC has exist-

ed since the 1980’s but has only recently started to be deployed in more than a minimal number of

cars. Thus, more actions are required to realize the potential of an ITS. The SAFESPOT project (TNO

et al., 2010) identifies the following issues that can play a role in deploying (cooperative) ITS:

organisational architecture and in particular roles and responsibilities;

risks and legal aspects;

impacts and cost-benefit assessment; and

business models and market assessment.

Still following SAFESPOT, a deployment analysis starts from the present situation, describing the cur-

rently available ITS and underlying technology, the current organizational setting and the current

trends towards the deployment of ITS systems. Deployment scenarios are selected by identifying im-

53

portant “scenario dimensions”, that is, the main choices that one wants to vary and investigate. These

could be concerned with various aspects, such as

Technical realization, e.g. personal devices versus road-side units.

Leading stakeholder(s), e.g. public or private.

Functional scope of the system, e.g. informing or intervening, information supply to authorities

or to the general public, real-time or historic.

Legal framework, e.g. mandatory or voluntary.

SAFESPOT has analysed the three choices private lead – public lead, V2V communication – V2I

communication and generic platform – dedicated platform. From this the following scenarios have

been selected:

1. Technology pushed ITS revolution: private lead, V2V communication, generic platform. This

scenario deploys a wide range of applications without government funding. Financing will

come from the end-user.

2. Safety as a public good: public lead, V2I communication, dedicated platform. This scenario

deploys a more restricted range of applications and roadside infrastructure, funded or subsi-

dized by the government. The deployment is expected to be retarded compared to the first

scenario.

3. Extended traffic management: public lead, V2I communication, generic platform. This scenario

deploys nomadic devices and roadside infrastructure, funded or subsidized by the govern-

ment. The deployment is expected to be similar to the first scenario.

For each scenario, deployment challenges are described for five broad categories:

a. How to reach critical mass so that a favourable business case and societal benefit-

cost ratio can be obtained.

b. How to develop a step by step deployment path, and thereby avoid large steps that

come with high investment and high risk.

c. How to realise a European market.

d. Which business case to adopt for the stakeholders.

e. How to realized cooperation between stakeholders.

The deployment analysis continues to identify and describe deployment scenarios in terms of seven

variables, namely:

1. The ITS applications for which the scenario is developed. Here one describes the application

or applications that are considered in the scenario. Multiple applications can be considered if

they will influence each other, for example if they run on the same platform.

2. The technology and system configuration. This variable lists important considerations in the

choice of technology. Such choices could be e.g. long-range versus short-range communica-

tion, or dedicated devices versus generic PDA’s. Considerations typically have to with quality

requirements (like accuracy, reliability, timeliness), performance requirements (like processing

power) or data access requirements.

3. The expected market penetration. This is often very difficult to estimate. A much used ap-

proach is to first estimate an average market penetration curve as a function of time, and then

shift it to get more optimistic and pessimistic scenarios. In this way, rather than trying to pre-

dict the market penetration one tries to assess the sensitivity of the deployment scenario. The

market penetration will depend heavily on the technology that is used, on user acceptance, on

54

government policy and on the legal framework. Market penetration can be translated into traf-

fic penetration (which fraction of kilometres is travelled with the ITS) with models similar to the

ones used in eIMPACT (Wilmink et al.,. 2008).

4. The business model. A business model describes how money, services and products flow be-

tween different stakeholders. Deployment of an ITS will only take off if all stakeholders benefit.

Benefits are often financial (and for industry stakeholders this is usually the main driver) but in

particular for governments social benefits may also play a role. Financial benefits can be indi-

rect: competitive edge, reputation, market share, valuable information, etc.

5. The organisational architecture. This describes the roles that stakeholders can play

(SAFESPOT identified 13 roles) and the interactions or exchanges between these roles. Roles

are for example Public authority, Service provider, several types of Suppliers, and Certificating

bodies. Exchanges can be about Data, Services, Products, Licenses and Rules. Roles are an

invariant of a deployment scenario, but the stakeholders performing them may change.

6. The societal costs and benefits. This assesses the costs and benefits of the application on so-

cietal level, including non-monetary costs and benefits such as changes in traffic safety, traffic

efficiency and environment, but not distributing costs and benefits over stakeholders. In princi-

ple, costs and benefits on other societal issues (e.g. employment, health) can also be taken

into account. This analysis determines whether the total societal benefits of an application in a

certain deployment scenario outweigh the costs, and hence whether a beneficial introduction

is possible in principle. It does not mean necessarily that all stakeholders will benefit, but may

provide some hints on potential benefits, key influencing factors, and promising business

models.

7. The legal framework. This does not only concern laws (the public legal framework), but also

private and mixed public-private legal frameworks like contracts, self-regulation and standardi-

sation. SAFESPOT also includes financial aspects like taxation and incentives in this frame-

work. A legal framework may provide a basis on which applications can be deployed, for ex-

ample by standardisation, regulating risks (e.g. liability) or establishing organizational struc-

tures. It may also force deployment via legal requirements, and it may change the deployment

environment, e.g. by adapting traffic laws.

A deployment road map describes a deployment scenario and the activities that are to be performed

by the various roles. It may also provide a time path or order for these activities. Activities can for ex-

ample be to develop standards or business models, to provide incentives, adapt the legal framework,

offer services or technical components, increase awareness, etc.

While the SAFESPOT methodology was developed for cooperative systems aiming at car drivers as

end users, it is also applicable to (cooperative or stand-alone) ITS that aim to be beneficial for VRU.

The SAFESPOT deployment scenarios and road map are too specific to be used one on one. Some

important differences between SAFEPOT and VRUITS are that

The SAFESPOT applications are all cooperative with an in-car component. VRUITS considers

both cooperative and stand-alone applications, and the cooperative ones do not have to have

an in-car component.

The SAFESPOT applications target car drivers as beneficiaries. In VRUITS car drivers may be

users of the applications, but the beneficiaries are pedestrians, cyclists or PTW riders.

The SAFESPOT applications are all aiming to improve safety. In VRUITS, the applications

may address safety, mobility and/or comfort.

55

Deployment of ITS for VRU

The main source of information on deployment scenarios and road maps for the ITS selected for

VRUITS are the answers to the questionnaires of section 4.2. Although only a small number of ques-

tionnaires were filled in, some tentative conclusions can be drawn from them as well as from the ex-

pertise of VRUITS experts:

Barriers that are mentioned are: costs, data security, technical complexity, lack of political in-

terest, lack of end user interest, lack of end user acceptability.

Legal mandate is mentioned as a driver.

A full deployment analysis of all VRUITS systems is not feasible within the limits of time and budget of

this task. But some remarks can be made on specific challenges for ITS for VRU’s, by comparing the

situation for VRU’s to the SAFESPOT analysis:

Willingness to pay: Car owners are used to spend a significant sum of money on new vehicles

and on maintenance, fuel, insurance etc. This makes it possible to include ITS systems as

add-on package with a new vehicle or (in a later stage) even in basic variants, and indeed this

is happening. However, this is usually limited to systems that actually benefit the car owners

themselves. It is much harder to convince them to pay for systems that benefit other road us-

ers (usually this concerns safety systems).

Pedestrians and cyclists are not used to spending much on their travel, and therefore are not

expected to spend significantly on ITS systems. This means that it will be difficult to create a

positive business case if it relies on large end user payments for systems aiming at cyclists

and pedestrians. This suggests that one should either aim for low cost solutions, for example

using existing devices like smart phones or low cost devices like tags, or devices need to be

subsidized by the government, or devices need to be made mandatory. This issue may be

less pronounced for PTW riders: there the C-ITS system can be implemented fixed in the

PTW.

Stakeholders: especially for pedestrians and to some extent also for cyclists, there are few

obvious stakeholders from the industry side. This means in particular that there are no obvious

parties that will invest heavily in ITS aiming at these VRUs. Regarding devices for VRUs, initi-

atives of the public sector may be needed to stimulate development of these devices. This

leads to the same conclusions on low cost solutions or government involvement as in the pre-

vious remark

User acceptance: For motorcyclists, freedom of action is an important aspect of their riding

experience. Applications that inhibit or seem to inhibit their freedom will meet low acceptance

rates. This is true in particular for any system that intervenes in the riding task, such as ISA

(Intelligent Speed Adaptation).

Other end user limitations: other important inhibitors to the deployment of ITS aiming at pe-

destrians and cyclists are power consumption, weight, size and (especially for on-bicycle de-

vices) risk of theft. These issues are less relevant for PTW riders.

Impacts and benefits: For many VRU-oriented devices it is not yet clear what their societal and

individual benefits will be. While the past years have seen significant research into the im-

pacts, benefits and costs of ITS aiming at car and truck drivers (ranging from desk research to

field operational tests, with EU projects like TRACE, PreVENT, eIMPACT, EuroFOT, Tele-

FOT, interactIVe, SAFESPOT, CVIS, Drive C2X and many others, and furthermore many na-

tional or local studies), there has been little research on the same topics for VRU oriented de-

vices. Much of the research that has been done is very local in nature and hard to generalize

to the EU level. This means that it is difficult to determine the technical feasibility, effective-

ness and societal benefits of devices. This is for example true for innovative concepts or sys-

56

tems like BRM (Cyclist digital bicycle rear-view mirror and rear obstacle detection), FOD (For-

ward obstacle detection for cyclists) and GWC (Green Wave for Cyclists). This suggests that

higher research effort on impacts will be needed as input for a proper deployment analysis.

Differences between countries: The take-up of ITS may be different in different European

countries and regions due to differences in travel culture, transport system, weather and cli-

mate, views on the role of governments, etc. For example, mandatory use of systems like ISA

or BSD (blind spot detection) may be more acceptable in some countries than in others. ITS

systems that warn for adverse weather conditions may be more useful in the north than in the

south. Countries or regions with significant numbers of cyclists may be more interested in bi-

cycle oriented systems. Advanced safety oriented ITS may be of more interest for those coun-

tries that have already applied more traditional safety measures like infrastructure improve-

ments. Some systems may be more appropriate for rural areas while others will aim for dense-

ly populated ones. While such differences also exist to some extent for car traffic, it seems

likely that for VRU’s they are more pronounced because VRU travel is usually more local, less

regulated, and more easily influenced by external circumstances like weather.

Differences between user groups: Road users have different abilities, aims and limitations,

depending on for example age and health. While this is also true for car drivers, it is a much

more pronounced issue for VRU’s. Some reasons for that are:

o Certain road users only appear as VRUs. This holds for example for children who are

not accompanied by an adult and hence have to travel by foot, bicycle, public

transport or possibly moped. It also holds for people with certain disabilities or physi-

cal limitations. This means on the one hand that one can expect a greater variation in

behaviour, and on the other hand that for certain people, travelling as VRU may be

their only choice of travelling – meaning that for social reasons extra care should be

taken that this choice remains available to them.

o Physical ability has a much larger influence on VRU travel than on car travel. There

are huge differences between (healthy) elderly pedestrians and middle-aged pedestri-

ans when it comes to walking speed, distances that can be walked, ability to deal with

obstacles, etc. There are similar issues for cyclists. Such differences may also appear

because of health impairments.

All in all this suggests that a private lead is only possible for low cost solutions based on existing de-

vices like smartphones, or possible for fixed installation in PTW’s. Any significant investments for the

benefit of pedestrians and cyclists will require government involvement, either financial or regulatory,

or both. For pedestrians and cyclists there may be further challenges regarding the technical feasibility

of solutions. Other challenges have to do with differences between countries and user groups.

57

5. DISCUSSION AND CONCLUSION

Concerning mobility and comfort forecasts, up until the year 2030 there is a trend towards a more pe-

destrian friendly environment by providing more space dedicated to this road user group. Technologi-

cal innovations in conjunction with spatial planning and improved public transport options in the urban

areas in Europe help to develop more car-free mobility profile for a broader range or road user groups.

This in turn is expected to change the modal split in the urban centres sustainably towards walking,

cycling and also PTWs.

With regard to safety trends, assuming that the current trends in road casualty numbers remain the

same until 2030 car occupant fatalities will decrease dramatically. However the predicted decrease for

the VRU groups is not so dramatic.

ITS applications are key to make transportation of VRUs safer and more comfortable. However, there

seems to be a gap between the ITS community and final users.

A study carried out by the European Commission reveals that a high rate of people is aware of some

ITS applications, but their willingness to buy a vehicle with these systems is highly dependable on the

final price (Kievit, 2008). In addition, pedestrians and cyclists are not used to spend much on their

travel, and therefore are not expected to spend significantly on ITS systems. In this sense existing de-

vices like smartphones might be good solution.

Smartphones are also a good alternative to in-vehicle technology, given that they have a high market

penetration which enables a fast deployment of the technology. This is especially relevant for coopera-

tive ITS, where a critical mass of vehicles equipped with technology is necessary to create a viable

business model. According to the Amsterdam Group (2013) retrofit and after-market equipment will be

able to support the development and penetration increase of cooperative ITS. However, smartphones

have difficulties to fulfil the low latency and accuracy requirements of safety applications.

The deployment of cooperative ITS needs a multi-stakeholder cooperation, and requires collaboration

among the cooperating organizations. For a cooperative ITS that requires a combination of in-vehicle

and infrastructure technology collaboration between the vehicle manufacturing industry and the infra-

structure providers will be required. Authorities are key players in cooperative systems deployment

(Amsterdam Group, 2013). The European Union and the national and local governments are the pri-

mary source of funding for ITS infrastructure technology. But an important principle guiding deploy-

ment is cost effectiveness. The cost-benefit relation of ITS systems has to be sufficient for authorities.

This is a key aspect for the deployment of ITS, and the thing is that the real benefits of cooperative

systems for local authorities have still to be proven.

A good starting point on a road map towards ITS for VRU is to investigate the potential impacts and

benefits of such systems. This project takes a first step in that direction. Further steps could be for

governments to organize and fund field trials to gain practical experience and raise awareness, to

harmonize the development in different countries where feasible and learn from each other’s exper i-

ences. As argued above, the role of governments in this development is significant and they may have

to take the lead in many cases.

58

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http://www.unece.org/data

ITS MARKET RESEARCH

60

Appendix A. Questionnaires on penetration rates

A.1 Questionnaire for authorities

ITS Market Research Questionnaire for authorities

Dear participant,

This survey shows a set of services in order to determine their feasibility, time frame for implementation, and the main

obstacles that must be overcome to achieve the deployment of ITS in European cities.

Your participation is very important to ensuring a complete and accurate tracking of ITS deployment in Europe.

Thank you for your assistance with this survey effort. Your cooperation is greatly appreciated.

ITS MARKET RESEARCH

61

Background Information

Job role/function: _________________________________

Institution: _______________________________________

City: ____________________________________________

Country: _________________________________________

ITS MARKET RESEARCH

62

ITS Survey

Please, answer the items below by selecting for each item the option that best reflects your opinion.

1. Intelligent Pedestrian Traffic Signal

IPTS is a traffic signal control system that uses sensors such as an infra-red camera to de-

termine the presence of pedestrians and adjusts the traffic signals accordingly. Scenarios

this system addresses are cyclist and pedestrian accidents at signalized intersections where

there is a zebra crossing.

VRUs are provided with enough time to cross the road (in traffic signals longer green time).

a. Does your Administration have any plans to invest in this

system in the future?

Yes No

(If the answer is Yes please go to question d)

b. Would your authority consider investing in this system in

the future?

Yes No


c. Would your authority consider co-financing or facilitating

private investments in this system (by providing space for

roadside infrastructure) in the future?

Yes No

d. How many of these systems do you estimate there will be

installed in your city by 2020? (absolute nº of systems and

percentage to the total nº of pedestrian crossings in the city)

Nº of systems

________

Percentage

______

e. How many of these systems do you estimate there will be

installed in your city by 2030?

Nº of systems

________

Percentage

________

f. How many of these systems do you estimate there will be in

your country by 2020?

Nº of systems

________

Percentage

________

g. How many of these systems do you estimate there will be

in your country by 2030?

Nº of systems

________

Percentage

________

h. How useful do you think is the implementation of this ser-

vice?

Why?

__________________________________________________

__________________________________________________

__________________________________________________

__________________________________________________

1 2 3 4 5 1. Not at all useful – 2. Not very useful - 3.Somewhat useful –

4. Quite useful - 5. very useful

ITS MARKET RESEARCH

63

i. Main obstacles: please select the main obstacles that must be overcome to achieve the deployment of this

ITS and provide a comment what the obstacle is

[] Technical _________________________________

[] Legal _____________________________________

[] Political___________________________________

[] Social ____________________________________

[] Economic _________________________________

[] Other (specify)_____________________________

j. Success factors: please comment what are the reasons why you think this ITS will be successfully introduced

in your country

k. Please use the space below to provide any additional comments regarding your institution´s deployment of

this ITS.

ITS MARKET RESEARCH

64

2. Intersection Safety

Intersection Safety assists the driver and VRU in avoiding common mistakes which

may lead to typical intersection accidents. It covers these functions: left and right

turn assistance and vehicles arriving perpendicular to VRUs at intersections.

For left- and right-turning assistance, RSU detects the VRU, communicates this to

the vehicle which is turning right or left into the path of the VRU. The vehicle driver

is informed; gets a warning or the vehicle begins to brake, depending on the urgen-

cy of the situation. The roadside infrastructure also informs the VRU of a dangerous

situation by eg flashing lights, and / or making a sound.

The second function identifies a dangerous situation in which the vehicle drives

perpendicular to the path of the VRU. The RSU detects the VRU crossing the inter-

section. The RSU informs the vehicle about the presence of the VRU. The RSU also

informs the VRU (via flashing lights/ sound) about the presence of the on-coming

vehicle.

a. Does your Administration have any plans to invest in this sys-

tem in the future?

Yes No


b. Would your authority consider investing in this system in the

future?

Yes No



private investments in this system (by providing space for road-

side infrastructure) in the future?

Yes No


installed in your city by 2020? (absolute nº of systems and per-

centage to the total nº of intersections in the city)

Nº of systems

________

Percentage

________



Nº of systems

________

Percentage

________


your country by 2020? (absolute nº of systems and percentage

to the total nº of pedestrian crossings in the country)

Nº of systems

________

Percentage

________

g. How many of these systems do you estimate there will be in


Nº of systems

________

Percentage

________

ITS MARKET RESEARCH

65


vice?

Why?

____________________________________________________

____________________________________________________

____________________________________________________

____________________________________________________



i. Main obstacles: please select the main obstacles that must be overcome to achieve the deployment of this ITS

and provide a comment what the obstacle is

[] Technical _________________________________

[] Legal _____________________________________

[] Political___________________________________

[] Social

____________________________________

[] Economic

_________________________________

[] Other (speci-

fy)_____________________________

j. Success factors: please comment what are the reasons why you think this ITS will be successfully introduced in

your country


this ITS.

ITS MARKET RESEARCH

66

3. Crossing Adaptive Lighting

Crossing Adaptive Lighting mounted at zebra crossings lights the zebra crossing when pe-

destrians and cyclists use it. When the pedestrian/cyclist activates the system, by through

detection from an automated device, the lights are activated / brightened to light the

crossing. The system increases the safety of zebra crossing users by increasing their visibil-

ity to drivers (reducing the chance that the pedestrian/cyclist is not or late observed by the

driver) and by making the crossing action safer for the pedestrians/cyclists due to the im-

proved lighting.



Yes No



the future?

Yes No





Yes No


installed in your city by 2020? (absolute nº of systems and

percentage to the total nº of pedestrian crossings in the city)

Nº of systems

______

Percentage

______



Nº of systems

________

Percentage

________



Nº of systems

________

Percentage

________



Nº of systems

________

Percentage

________


vice?

Why?

__________________________________________________

________________________________________________



ITS MARKET RESEARCH

67



[] Technical _________________________________

[] Legal _____________________________________

[] Political___________________________________

[] Social ____________________________________

[] Economic _________________________________

[] Other (specify)_____________________________


in your country


this ITS.

ITS MARKET RESEARCH

68

4. VRU Beacon System

The VRU has a tag or device that sends out a signal that can be detected by a device in-

stalled in vehicles or infrastructure. This system calculates the trajectories of the detected

VRU, in relation with the vehicle trajectory and assesses the possibility of a collision. The

driver is then warned about the possible collision. Practical example: this system is current-

ly used in warehouses to prevent accidents between forklifts and pedestrians. The VRU has

a device transmitting C-ITS (cooperative traffic compliant) messages, which could be a

device fixedly installed on the VRU device or a smart-phone with a specific app. The receiv-

ing equipment and the collision assessment are installed in either vehicles or roadside in-

frastructure. The vehicle only warns the driver, no intervention.



Yes No



the future?

Yes No





Yes No

d. How many of these systems do you estimate there will

be installed in your city by 2020? (absolute nº of systems

and percentage to the total nº of pedestrian crossings in the

city)

Nº of systems

________

Percentage

________

e. How many of these systems do you estimate there will

be installed in your city by 2030?

Nº of systems

_______

Percentage

________

f. How many of these systems do you estimate there will be

in your country in 2020? (absolute nº of systems and per-

centage to the total nº of pedestrian crossings in the coun-

try)

Nº of systems

_______

Percentage

________


in your country in 2030?

Nº of systems

________

Percentage

________

ITS MARKET RESEARCH

69

h. How useful do you think is the implementation of this

service?

Why?

_________________________________________________

_________________________________________________

_________________________________________________

_________________________________________________

1 2 3 4 5 1. Not at all useful – 2. Not very useful - 3.Somewhat useful – 4.

Quite useful - 5. very useful



[] Technical _________________________________

[] Legal _____________________________________

[] Political___________________________________

[] Social ____________________________________

[] Economic _________________________________

[] Other (specify)_____________________________


in your country


this ITS.

ITS MARKET RESEARCH

70

5. Information on vacancy on bicycle racks

The system provides information on the number of and closest

available parking spaces for bicycles.

Systems are today available (see e.g. Seattle, US) that are based

on a free phone app that allows users to quickly locate a nearby

city-installed bike rack. It’s described as fast, responsive and easy

to use (figure).

Next step is to inform the bicyclists if there is any free parking at

the specific location.

Suitable to be placed at for example: stations for public transport,

parking garages, work places, apartment buildings, shopping cen-

tres and hotels. In this study the focus is on a system integrated

with a locking system for the bike.



Yes No



the future?

Yes No



private investments in this system in the future?

Yes No

d. How many cyclists do you estimate will have this system

in your city by 2020? (absolute nº of systems and percent-

age to the total nº of cyclists in the city)

Nº of systems

_________

Percentage

_________

e. How many cyclists do you estimate will have this system

in your city by 2030?

Nº of systems

__________

Percentage

________

f. How many cyclists do you estimate will have this system


Nº of systems

__________

Percentage

_________

g. How many cyclists do you estimate will have this system


Nº of systems

_________

Percentage

________

ITS MARKET RESEARCH

71

h. How useful do you think is the implementation of this

service?

Why?

_________________________________________________

_________________________________________________

_________________________________________________

_________________________________________________





[] Technical _________________________________

[] Legal _____________________________________

[] Political___________________________________

[] Social ____________________________________

[] Economic _________________________________

[] Other (specify)_____________________________


in your country


this ITS.

ITS MARKET RESEARCH

72

6. Green Wave for cyclists

Cyclists receive a speed advice; if they follow it, they are guaranteed a green light at the

next controlled intersection.

The speed advice is provided via a personal device (a smart-phone or a bicycle computer).

The system needs to know the location of the cyclist, which should be determined by the

personal device. If the cyclist’s route information is available, the system will work better

because it can anticipate whether to provide a green wave for the next intersection(s).

Advanced versions of the system may even adapt the traffic light control scheme. The

speed advice can be provided as feedback (compared to current speed). The module de-

termining the speed advice is located in the personal device.

The system is easiest to implement in case of a fixed time traffic light controller. First re-

search results indicate the possibility of supporting adaptive time traffic light controllers

as well.



Yes No



the future?

Yes No



private investments in this system in the future?

Yes No


in your city by 2020? (absolute nº of systems and percentage

to the total nº of cyclists in the city)

Nº of systems

________

Percentage

________



Nº of systems

________

Percentage

________


your country in 2020?

Nº of systems

________

Percentage

________

ITS MARKET RESEARCH

73


in your country in 2030?

Nº of systems

________

Percentage

________


vice?

Why?

__________________________________________________

__________________________________________________

__________________________________________________

__________________________________________________



i. Main obstacles: please select the main obstacles that must be overcome to achieve the deployment of this ITS


[] Technical _______________________________

[] Legal ___________________________________

[] Political_________________________________

[] Social ____________________________________

[] Economic _________________________________

[] Other (specify)_____________________________

j. Success factors: please comment what are the reasons why you think this ITS will be successfully introduced in

your country


this ITS.

THANK YOU VERY MUCH FOR PARTICIPATING

ITS MARKET RESEARCH

74

A.2 Questionnaire for manufacturers

ITS Market Research Questionnaire for manufacturers

Dear participant,

This survey is designed to obtain data measuring the level of Intelligent Transportation System (ITS) deployment in Eu-

rope. The results of this survey will be used by the VRUITS project to establish the extent of ITS deployment in the follow-

ing years. More information about VRUITS can be found on our website: http://www.vruits.eu/

This survey is designed to obtain data measuring the level of Intelligent Transportation System (ITS) deployment in Eu-

rope. The results of this survey will be used by the VRUITS project to establish the extent of ITS deployment in the follow-

ing years. More information about VRUITS can be found on our website: http://www.vruits.eu/

This survey shows a set of services in order to determine their feasibility, time frame for implementation, and the main

obstacles that must be overcome to achieve the deployment of ITS in European cities.

Your participation is very important to ensuring a complete and accurate tracking of ITS deployment in Europe.

Thank you for your assistance with this survey effort. Your cooperation is greatly appreciated.



ITS MARKET RESEARCH

75

Background Information

Job role/function: _________________________________

Company: _______________________________________

City: ____________________________________________

Country: ________________________________________

ITS MARKET RESEARCH

76

ITS Survey

Please, answer the items below by selecting for each item the option that best reflects your opinion.

1. VRU Beacon System

The VRU has a tag or device that sends out a signal that can be detected by a device installed in vehicles or infrastructure. This system

calculates the trajectories of the detected VRU, in relation with the vehicle trajectory and assesses the possibility of a collision.

The VRU has a device, which is able to transmit C-ITS (cooperative traffic) compliant messages. and the vehicle has a standard C-ITS

unit, which is able to receive the messages sent by VRUs. The receiving equipment and the collision assessment are installed in either

vehicles or roadside infrastructure. The vehicle only warns the driver, no intervention.

Vehicles with OEM systems Vehicles with retrofit / nomadic systems

a. How many passenger cars do you estimate will be equipped with

this system in your country by 2020? (absolute nº of systems and

percentage to the total nº of passenger cars)

Nº of systems

__________

Percentage

__________

Nº of systems

___________

Percentage

__________


b. How many passenger cars do you estimate will be equipped with

this system in your country by 2030?

Nº of systems

____________

Percentage

___________

Nº of systems

____________

Percentage

___________

Pedestrians with Cooperative devices

c. How many pedestrians do you estimate will have this system in

your country by 2020? (absolute nº of pedestrians and percentage to

the total nº of pedestrians in the city)

Nº of systems

____________

Percentage

__________

Pedestrians with Cooperative devices

ITS MARKET RESEARCH

77

d. How many pedestrians do you estimate will have this system in


Nº of systems

___________

Percentage

___________

Bicycles with Cooperative devices

e. How many cyclists do you estimate will have this system in your

country by 2020?

Nº of systems

____________

Percentage

____________

f. How many cyclists do you estimate will have this system in your

country by 2030?

Nº of systems

____________

Percentage

____________

PTW´s (with Cooperative devices)

g. How many PTW´s do you estimate will have this system in your

country by 2020?

Nº of systems

____________

Percentage

____________

h. How many PTW´s do you estimate will have this system in your

country by 2030?

Nº of systems

____________

Percentage

____________

i. Main obstacles: please select the main obstacles that must be overcome to achieve the deployment of this ITS and provide a comment what the obstacle is

[] Technical __________________________________________________

[] Legal ______________________________________________________

[] Political ____________________________________________________

[] Social _____________________________________________________

[] Economic __________________________________________________

[] Other (specify) ______________________________________________

j. Success factors: please comment what are the reasons why you think this ITS will be successfully introduced in your country

k. Please use the space below to provide any additional comments regarding the deployment of this ITS in your country

ITS MARKET RESEARCH

78

2. Bicycle to car communication

Inform and warn cyclists of potential collisions with vehicles, and inform

the vehicle driver about cyclists on the road, in the vicinity of the vehi-

cle. Cyclists can receive information about oncoming vehicles and can be

warned about the risk of collisions, on their mobile device (smart-

phone).

The vehicle needs to be equipped with a standard C-ITS unit to send and

receive messages with bicyclists (i.e. the same equipment as for the VRU

beacon system)

Cyclists

a. How many cyclists do you estimate will have this system in


Nº of systems

________

Percentage

________

Cyclists

b. How many cyclists do you estimate will have this system in


Nº of systems

____________

Percentage

____________

c. Main obstacles: please select the main obstacles that must be overcome to achieve the deployment of this ITS


[] Technical __________________________________

[] Legal ___________________________________________

[] Political ________________________________________________

[] Social _____________________________________________________

[] Economic __________________________________________________

[] Other (specify) ______________________________________________

d. Success factors: please comment what are the reasons why you think this ITS will be successfully introduced in

your country

e. Please use the space below to provide any additional comments regarding the deployment of this ITS in your

country

ITS MARKET RESEARCH

79

3. PTW oncoming vehicle information system

The aim with Honda Advanced Safety Vehicle (ASV) is to help address

lapses of attention in ways that single-vehicle systems cannot. It is the

problem of visibility and awareness of motorcycles on the road that is

addressed, both from MC-driver-perspective and vehicle driver-

perspective. The following examples on how the system helps the

drivers are based on situations in Japan, i.e. left hand side traffic:

The drivers are focusing on traffic from one direction when travelling

through an intersection, and misses traffic/MC from different direc-

tions. The driver (both car driver and MC-driver) is informed about the

other vehicle, based on communication between the vehicles/MC.

Hence, both the car drivers and MC-drivers can slow down or change

their driving/steering to avoid the collision.

The vehicle is equipped with a standard C-ITS device.

a. How many PTW´s do you estimate will have this system in

your country by 2020? (absolute nº of PTW´s and percentage to

the total nº of PTW´s)

Number of PTW´s

_______

Percentage

________

b. How many PTW´s do you estimate will have this system in


Number of PTW´s

________

Percentage

________

c. How many passenger cars do you estimate will have this sys-

tem in your country by 2020?

Number of cars

________

Percentage

________

d. How many passenger cars do you estimate will have this sys-

tem in your country by 2030?

Number of cars

________

Percentage

________

e. Main obstacles: please select the main obstacles that must be overcome to achieve the deployment of this


[] Technical ___________________________________

[] Legal _______________________________________

[] Political _____________________________________

[] Social ___________________________________

[] Economic ________________________________

[] Other (specify) ____________________________

f. Success factors: please comment what are the reasons why you think this ITS will be successfully introduced

in your country

g. Please use the space below to provide any additional comments regarding the deployment of this ITS in

your country

ITS MARKET RESEARCH

80

4. Information on vacancy on bicycle racks

The system provides information on the number of and closest available parking

spaces for bicycles.

Systems are today available (see e.g. Seattle, US) that are based on a free phone

app that allows users to quickly locate a nearby city-installed bike rack. It’s de-

scribed as fast, responsive and easy to use (figure).

Next step is to inform the bicyclists if there is any free parking at the specific loca-

tion.

Suitable to be placed at for example: stations for public transport, parking garages,

work places, apartment buildings, shopping centres and hotels. In this study the

focus is on a system integrated with a locking system for the bike.

a. How many cyclists do you estimate will have this system in


Nº of cyclists

___________

Percentage

____________

b. How many cyclists do you estimate will have this system in


Nº of cyclists

___________

Percentage

____________

c. Main obstacles: please select the main obstacles that must be overcome to achieve the deployment of this ITS


[] Technical _______________________________________

[] Legal __________________________________________

[] Political ________________________________________

[] Social ________________________________

[] Economic _____________________________

[] Other (specify) _________________________

d. Success factors: please comment what are the reasons why you think this ITS will be successfully introduced

in your country

e. Please use the space below to provide any additional comments regarding the deployment of this ITS in your

country

ITS MARKET RESEARCH

81

5. Green Wave for cyclists

Cyclists receive a speed advice; if they follow it, they are guaranteed a

green light at the next controlled intersection.

The speed advice is provided via a personal device (a smart-phone or a

bicycle computer). The system is I2VRU, and the advice is personalized,

taking into account e.g. personal speed preferences or (recent) history.

The system needs to know the location of the cyclist, which should be de-

termined by the personal device. If the cyclist’s route information is avail-

able, the system will work better because it can anticipate whether to pro-

vide a green wave for the next intersection(s). Advanced versions of the

system may even adapt the traffic light control scheme. The speed advice

can be provided as feedback (compared to current speed). The module

determining the speed advice is located in the personal device.

a. How many cyclists do you estimate will have

this system in your country by 2020? (absolute nº

of cyclists and percentage to the total nº of cy-

clists)

Nº of cyclists

____________

Percentage

____________

b. How many cyclists do you estimate will have


Nº of cyclists

____________

Percentage

____________

c. Main obstacles: please select the main obstacles that must be overcome to achieve the deployment of

this ITS and provide a comment what the obstacle is

[] Technical __________________________________

[] Legal _____________________________________

[] Political ___________________________________

[] Social ________________________________

[] Economic _____________________________

[] Other (specify) _________________________

d. Success factors: please comment what are the reasons why you think this ITS will be successfully in-

troduced in your country

e. Please use the space below to provide any additional comments regarding the deployment of this ITS

in your country

ITS MARKET RESEARCH

82

6. Intersection Safety

Intersection Safety assists the driver and VRU in avoiding common mistakes which may lead to typical intersection accidents. It

covers these functions: left and right turn assistance and vehicles arriving perpendicular to VRUs at intersections.

For Left- and right-turning assistance, RSU detects the VRU, communicates this to the vehicle which is turning right or left into

the path of the VRU. The vehicle driver is informed; gets a warning or the vehicle begins to brake, depending on the urgency of

the situation. The roadside infrastructure also informs the VRU of a dangerous situation by e.g. flashing lights. And / or making

a sound.

The second function identifies a dangerous situation in which the vehicle drives perpendicular to the path of the VRU. The RSU

detects the VRU crossing the intersection. The RSU informs the vehicle about the presence of the VRU. The RSU also informs

the VRU (via flashing lights/ sound) about the presence of the on-coming vehicle.


a. How many passenger cars do you estimate will be equipped

with this system in your country by 2020? (absolute nº of sys-

tems and percentage to the total nº of cars)

Nº of systems

____________

Percentage

____________

Nº of systems

____________

Percentage

____________


b. How many passenger cars do you estimate will be equipped

with this system in your country by 2030?

Nº of systems

____________

Percentage

____________

Nº of systems

____________

Percentage

____________


c. How many goods vehicles do you estimate will be equipped


Nº of systems

____________

Percentage

____________

Nº of systems

____________

Percentage

____________

ITS MARKET RESEARCH

83


d. How many goods vehicles do you estimate will be equipped


Nº of systems

____________

Percentage

____________

Nº of systems

____________

Percentage

____________


e. How many buses do you estimate will be equipped with this

system in your country by 2020?

Nº of systems

____________

Percentage

____________

Nº of systems

____________

Percentage

____________


f. How many buses do you estimate will be equipped with this


Nº of systems

____________

Percentage

____________

Nº of systems

____________

Percentage

____________

i. Main obstacles: please select the main obstacles that must be overcome to achieve the deployment of this ITS and provide a comment what the obstacle is

[] Technical __________________________________________________

[] Legal ______________________________________________________

[] Political ____________________________________________________

[] Social ___________________________________________________________

[] Economic ________________________________________________________

[] Other (specify) ____________________________________________________

j. Success factors: please comment what are the reasons why you think this ITS will be successfully introduced in your country

k. Please use the space below to provide any additional comments regarding the deployment of this ITS in your country

ITS MARKET RESEARCH

84

7. Blind Spot Detection

Blind Spot Detection (BSD) system uses vehicle sensor technology to detect pedestrians, bicyclists and PTWs in blind spots round the vehicle

based on vehicle sensors (mainly addressing the side areas, optionally front and rear). After the detection of VRUs or other objects in the blind

spot of the vehicle the system provides a warning to the driver.


a. How many passenger cars do you estimate will be equipped

with this system in your country by 2020? (absolute nº of sys-

tems and percentage to the total nº of cars)

Nº of systems

____________

Percentage

____________

Nº of systems

____________

Percentage

____________


b. How many passenger cars do you estimate will be equipped


Nº of systems

____________

Percentage

____________

Nº of systems

____________

Percentage

____________


c. How many goods vehicles do you estimate will be equipped


Nº of systems

____________

Percentage

____________

Nº of systems

____________

Percentage

____________


d. How many goods vehicles do you estimate will be equipped


Nº of systems

____________

Percentage

____________

Nº of systems

____________

Percentage

____________

ITS MARKET RESEARCH

85

Vehicles with OEM systems

Vehicles with retrofit / nomadic systems

e. How many buses do you estimate will be equipped with this


Nº of systems

____________

Percentage

____________

Nº of systems

____________

Percentage

____________


f. How many buses do you estimate will be equipped with this


Nº of systems

____________

Percentage

____________

Nº of systems

____________

Percentage

____________

g. Main obstacles: please select the main obstacles that must be overcome to achieve the deployment of this ITS and provide a comment what the obstacle is

[] Technical __________________________________________________

[] Legal ______________________________________________________

[] Political ____________________________________________________

[] Social ___________________________________________________________

[] Economic ________________________________________________________

[] Other (specify) ____________________________________________________

h. Success factors: please comment what are the reasons why you think this ITS will be successfully introduced in your country

i. Please use the space below to provide any additional comments regarding the deployment of this ITS in your country

86

8. Pedestrian Detection System + Emergency Braking

The vehicle has a built-in system that continuously scans for VRUs that

the vehicle might be in collision course with. If a crash is likely, the

system will warn the driver, for instance through sound, visual signals

or vibration of the steering wheel (there is also a variation of the sys-

tem that tightens the drivers’ seat belt, both as a warning and as a

safety feature). This system is working regardless the speed, but max-

imises its impact for lower speeds.

If the driver fails to respond in time, through steering away or through

braking, the system can intervene through braking. At low speeds this

variation system is intended to prevent a collision, at higher speeds

the system should reduce the impact of the crash.

a. How many passenger cars do you estimate will be equipped with

this system in your country by 2020? (absolute nº of systems and per-

centage to the total nº of passenger cars)

Nº of systems

____________

Percentage

____________

b. How many passenger cars do you estimate will be equipped with


Nº of systems

____________

Percentage

____________

c. How many goods vehicles do you estimate will be equipped with


Nº of systems

____________

Percentage

____________

d. How many goods vehicles do you estimate will be equipped with


Nº of systems

____________

Percentage

____________

e. How many buses do you estimate will be equipped with this system


Nº of systems

____________

Percentage

____________

87

f. How many buses do you estimate will be equipped with this system


Nº of systems

____________

Percentage

____________

i. Main obstacles: please select the main obstacles that must be overcome to achieve the deployment of

this ITS and provide a comment what the obstacle is

[] Technical _______________________________________

[] Legal __________________________________________

[] Political ________________________________________

[] Social ______________________________

[] Economic ___________________________

[] Other (specify) ______________________

j. Success factors: please comment what are the reasons why you think this ITS will be successfully intro-

duced in your country

k. Please use the space below to provide any additional comments regarding the deployment of this ITS in

your country

THANK YOU VERY MUCH FOR PARTICIPATING

D2.3


Appendix B.

Vehicle park Europe-28

88

Appendix B. Vehicle park Europe-28

B.1 Vehicle Park

D2.3


Appendix B.


89

B.2 New registrations

B.2.1 Passenger cars new registration in Europe 2013

D2.3


Appendix B.


90

B.2.2 Light Commercial (up to 3.5t) Vehicles new registration in Europe 2013

D2.3


Appendix B.


91

B.2.3 Heavy Commercial Vehicles (over 3.5t) new registration in Europe 2013

D2.3


Appendix B.


92

B.2.4 Light Buses and Coaches (up to 3.5t) new registration in Europe 2013

D2.3


Appendix B.


93

B.2.5 Heavy Buses and Coaches (over 3.5t) new registration in Europe 2013

D2.3


Appendix B.


94

B.3 PTWs registration in Europe 2008-2012

Source: The Motorcycle Industry in Europe, Statistical overview registrations, deliveries and circulating park. ACEM 2013

D2.3


Appendix B.


95

B.4 Bicycle sales in Europe 2012

Source: EUROPEAN BICYCLE MARKET 2013 edition, Industry & Market Profile 2012 statistics, Colibi

& Coliped.

D2.3


Appendix C.

Mobility data – overview of available mobility survey data of

selected European countries

96

Appendix C. Mobility data – overview of available mobility survey data of selected European

countries

Country Name of survey (year) Source (web adress)

Germany MID-Mobilität in Deutsch-

land (2008)

Federal Ministry of Transport, Building and Urban Affairs

(http://www.mobilitaet-in-deutschland.de/pdf/MiD2008_Abschlussbericht_I.pdf)

Switzerland Mikrozensus (2005) Federal Office for Spatial Development ARE

(http://www.are.admin.ch/dokumentation/publikationen/00024/00419/index.html?lang=de&download=NHzLpZeg7t,lnp6I0NTU042l2

Z6ln1acy4Zn4Z2qZpnO2Yuq2Z6gpJCDfH5,fmym162epYbg2c_JjKbNoKSn6A--)

Finland National Travel Survey

(2010-2011)

Finish Transport Agency (http://portal.liikennevirasto.fi/portal/page/portal/C2F9146F42766086E040B40A1A01194A)

Sweden National Travel Survey

(2012-2013)

Transport Analysis – Official Statistics of Sweden

(http://www.trafa.se/PageDocuments/RVU_Sverige_2013.pdf)

Estonia No survey European Comission - Eurostat

(http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=tran_hv_psmod&lang=en)

Lithuania No survey European Comission - Eurostat


Latvia No survey European Comission - Eurostat


England/UK National Travel Survey

(2012)

Department for Transport

(https://www.gov.uk/government/statistics/national-travel-survey-2012)

Malta NHTSA (2010) Transport Malta

(http://www.transport.gov.mt/admin/uploads/media-library/files/NHTS2010%20Report.pdf_20120502091559.pdf)

Spain MOVILIA (2006-2007) Minesterio de Fomento

(http://www.fomento.gob.es/NR/rdonlyres/2D1D40A2-3417-4C74-AF3F-D22D3A161F96/110679/Movilia20062007.pdf)

Northern Ireland Travel Survey (2011-

2013)

Department for Regional Development

(http://www.drdni.gov.uk/tsni_headline_report_2011-2013.pdf)

The Netherlands Mobiliteitsonderzoek

(2007)

Modal split data from: Ministerie van Verkeer en Waterstaat

(http://www.fietsberaad.nl/library/repository/bestanden/CyclingintheNetherlands2009.pdf)

D2.3


Appendix C.



97

Germany

Modal split (base: trips)

Pedestrian 23%

Cyclist 10%

Motorized private transport (driver) 47%

Motorized private transport (passenger) 12%

Public transport 9%

Average length paths (km) (total: 11,5 km)

Pedestrian 1.4

Cyclist 3.2

Motorized private transport (driver) 14.7

Motorized private transport (passenger) 18.3

Public transport 12.3

Average path time (min) (total: 24 min)

Pedestrian 23

Cyclist 19

Motorized private transport (driver) 21

Motorized private transport (passenger) 25

Public transport 41

Trip purpose

Work 15%

Education 4%

Business 7%

Shopping 38%

Free time 35%

D2.3


Appendix C.



98

Modal spilt by age

Age Cyclist Pedestrian Motorized pri-vate transport (driver)

Motorized pri-vate transport (passenger)

Public transport

To 17 years 14% 29% 1% 41% 14%

18-29 years 8% 20% 47% 12% 13%

30-39 years 9% 21% 56% 8% 6%

40-49 years 9% 18% 59% 8% 5%

50-59 years 9% 20% 55% 10% 6%

60-64 years 11% 26% 47% 11% 5%

65-74 years 10% 32% 39% 12% 6%

Over 74 years 7% 38% 31% 12% 11%

Mobility parameters by age and gender

Age Number of trips per day Total travel time (min) Daily travel length (km)

male female male female male female

0-10 years 3 3 65 62 24 24

11-13 years 3 3 73 69 28 23

14-17 years 2.9 3.2 76 85 27 33

18-29 years 3.7 3.5 86 87 51 47

30-39 years 3.8 3.9 85 81 65 39

40-49 years 3.9 3.9 88 82 62 40

50-59 years 3.7 3.4 85 78 57 32

60-64 years 3.7 3.3 85 80 37 33

65-74 years 3.5 3 87 75 33 23

Older than 75 years 2.7 2 69 50 20 12

D2.3


Appendix C.



99

Modal split share by gender and age in sector public transport, pedestrian and bicycle

Men

Age Pedestrian Bicycle Public transport

To 10 years 31% 11% 8%

11-17 years 23% 24% 23%

18-39 years 18% 9% 10%

40-64 years 17% 9% 5%

65-74 years 28% 11% 4%

Older than 75 years 34% 7% 8%

Women

Age Pedestrian Bicycle Public transport

To 10 years 33% 9% 7%

11-17 years 25% 17% 25%

18-39 years 23% 8% 9%

40-64 years 23% 10% 6%

65-74 years 36% 10% 8%

Older than 75 years 43% 7% 15%

Finland

Modal Split (base: trips)

Passenger Cars 58%

Non-Motorized 30%

Other Private 4%

Public Transport 8%

mean trip length (in km)

Passenger Cars 29.9

Non-Motorized 1.8

Public Transport 8

total 41.4

D2.3


Appendix C.



100

mean trip duration (in min)

Passenger Cars 34.4

Non-Motorized 17.6

Public Transport 10.6

total 65.5

Trip purpose

Work 17.30%

School, studies 7.10%

Business 3.50%

Shopping, personal business 34.50%

Visits 10.40%

Summer cottage 1.40%

Other leisure 24.30%

Total domestic and international travel distance (km/person/day)

Child, 6-14years old 40

Teen, 15-17 years old 33

Grown-up student 39

Works, no small children 83

Works, has small children 79

Housewife, househusband 34

18-64 y. doesn`t work or study 41

65-74 years old 31

Older than 74 years 17

On average 58

D2.3


Appendix C.



101

Sweden


Foot,Bicycle 31.30%

Car 52.50%

Public Transport 12.30%

Other Mode of Travel 2.30%

No Information 1.60%

Total time travelled (min)

Foot,Bicycle 31

Car 44

Public Transport 63

Other Mode of Travel 106

Total distance travelled (km)

Foot,Bicycle 2.9

Public Transport 36

Other Mode of Travel 306

Trip purpose

By foot, bicycle Car Public transport

Other mode of travel

Information not available

All

Business, work and study-related

574 579 1 134 047 425 537 43 222 39 312 2 216 696

Service and shopping 163 892 389 318 37 898 6 178 5 217 602 502

Leisure 630 518 658 318 75 342 40 446 22 044 1 427 047

Other purpose 51 704 198 808 17 276 12 417 9 190 289 395

Information not available 0 990 335 295 0 1 620

All 1 420 691 2 381 861 556 387 102 557 75 763 4 537 258

D2.3


Appendix C.



102

Number of journeys per per-son and day by gender, age and main purpose

Male Business, work and study-related

Service and shopping

Leisure Other purpose Information not available

All

Age

6-14 years 0.9 0.06 0.5 0.07 0 1.53

15-24 years 0.91 0.1 0.43 0.11 0 1.56

25-34 years 0.84 0.16 0.44 0.1 0 1.57

35-44 years 0.95 0.16 0.41 0.07 0 1.63

45-54 years 0.94 0.21 0.48 0.07 0 1.72

55-64 years 0.75 0.21 0.45 0.09 0 1.52

65-74 years 0.13 0.32 0.65 0.18 0 1.28

0.03 0.28 0.51 0.14 0 0.96

All 0.74 0.18 0.48 0.1 0 1.52

Female Business, work and study-related

Service and shopping

Leisure Other purpose Information not available

All

Age

6-14 years 0.96 0.11 0.48 0.1 0 1.66

15-24 years 0.88 0.12 0.46 0.13 0 1.6

25-34 years 0.77 0.21 0.55 0.07 0 1.6

35-44 years 0.92 0.25 0.52 0.1 0 1.79

45-54 years 0.95 0.19 0.58 0.07 0 1.8

55-64 years 0.75 0.24 0.51 0.07 0 1.58

65-74 years 0.06 0.29 0.6 0.09 0 1.04

75-84 years 0 0.25 0.4 0.08 0 0.73

All 0.71 0.21 0.52 0.09 0 1.54

D2.3


Appendix C.



103

Total distance travelled (km) per person and day by gender, age and main mode

Male By foot, bicycle Car Public transport Other mode of travel


All

Age

6-14 years 0.9 16 3 15 0 34

15-24 years 1.8 19 12 1 0 32

25-34 years 1.9 35 8 5 0 50

35-44 years 1.9 42 8 7 0 59

45-54 years 1.7 46 5 47 0 100

55-64 years 1.7 38 6 14 0 60

65-74 years 1.8 26 2 4 0 35

75-84 years 1.3 17 3 4 0 25

All 1.7 31 6 12 0 52

Female By foot. bicycle Car Public transport Other mode of travel


All

Age

6-14 years 1.2 22 2 4 0 30

15-24 years 2.1 15 10 3 0 30

25-34 years 2.2 24 11 31 0 68

35-44 years 1.9 29 6 4 0 42

45-54 years 2.2 27 7 3 0 38

55-64 years 2 26 5 3 0 36

65-74 years 1.6 19 3 1 0 25

75-84 years 0.8 8 3 1 0 13

All 1.8 22 6 6 0 37

D2.3


Appendix C.



104

Switzerland


Private transport 37.10%

Public transport 11.50%

Pedestrian and bicycle 50.20%

Other 1.20%

Distance travelled per person and day (km)

Private transport 26.2


Pedestrian and bicycle 2.8

Other 1.2

Duration for travel (min)

Private transport 40.7


Pedestrian and bicycle 44.4

Other 3.8

Mobility parameters per person and day

Average daily dis-tance

Average daily travel time

Average daily trips

Age

6-17 years 22.5 79.9 3.4

18-25 years 53 101.9 3.5

26-65 years 42.4 93 3.4

older than 66 years 21.2 70.1 2.4

male 43.9 96.1 3.4

female 31 81.1 3.2

Average 37.3 88.4 3.3

D2.3


Appendix C.



105

Trip purpose

Work 23.40%

Education 4.00%

Shopping 11.40%

Leisure 44.70%

Service and accompaniment 1.40%

Business 8.60%

Other 6.60%

UK


Car (passenger) 22%

Walk 22%

Bus 6%

Rail 3%

Bicycle 2%

Other 2%

Trip purpose

Shopping 20%

Education 12%

Business 3%

Commuting 15%

Other leisure 15%

Visiting friends 15%

Other escort and personal business 19%

D2.3


Appendix C.



106

Average number of trips by age and main mode (trips per person per year)

Walk Bicycle Car (driver) Car (pas-senger)

Other private transport

Local and non-local buses

Rail Taxi/minicab Other public transport

Age

0-16 years 269 11 0 461 16 67 10 7 2

17-20 years 207 20 151 186 11 142 40 21 6

21-29 years 203 22 358 147 7 70 64 13 4

30-39 years 225 19 543 135 5 45 55 10 5

40-49 years 185 19 632 115 9 49 32 8 3

50-59 years 168 12 587 140 10 42 27 10 2

60-69 years 180 10 513 166 9 60 17 8 2

Older than 70 years

139 5 309 161 8 85 7 10 2

D2.3


Appendix C.



107

Average number of trips by age and main mode (trips per person per year) distin-guished by gen-der

Male Walk Bicycle Car (driver) Car (passen-ger)




Age

0-16 years 256 15 0 449 19 64 10 7 2

17-20 years 196 37 152 164 11 117 30 14 7

21-29 years 169 28 355 116 14 57 71 11 7

30-39 years 176 30 525 98 8 38 67 12 5

40-49 years 168 31 618 61 13 31 40 6 2

50-59 years 156 18 661 66 15 33 31 10 1

60-69 years 190 15 650 69 8 50 18 8 2

Older than 70 years

153 9 491 78 10 74 8 6 2

Female Walk Bicycle Car (driver) Car (passen-ger)




Age

0-16 years 282 6 0 474 13 69 9 8 1

17-20 years 219 3 149 208 11 168 51 29 4

21-29 years 237 15 362 178 1 84 57 14 2

30-39 years 272 9 561 172 2 52 43 9 4

40-49 years 201 8 646 166 6 67 23 10 4

50-59 years 180 6 514 213 4 50 23 10 3

60-69 years 171 5 383 258 9 69 16 9 1

Older than 70 years

129 3 166 226 7 93 6 13 2

D2.3


Appendix C.



108

The Netherlands


Car 48%

Train 2%

Bus/Metro/Tram 3%

Walking 19%

Bicycle 26%

Trip purpose

Bicycle Pedestrian Car Other Total

Excursion 16% 59% 11% 6% 11%

Leisure and social 31% 14% 50% 6% 12%

Visit and overnight 21% 14% 60% 5% 14%

Education 50% 18% 18% 14% 9%

Shopping 28% 18% 49% 5% 20%

Service and personal care 18% 18% 55% 9% 4%

Busines 11% 3% 79% 7% 3%

Work 25% 4% 62% 10% 17%

D2.3


Appendix C.



109

Malta

Modal Split (base: trips)

Car Driver 59.40%

Car Passenger 15.20%

Bus 11.30%

Minibus/Coach 3.70%

Motorbike 1.10%

On Foot 7.60%

Other 1.70%

Time taken for trip in min

Car 19.3

Bus 33.5

Trip purpose (bus)

Visit someone 10.70%

Work place 16.50%

Work purposes 3.10%

Medical 6.20%

Private 13.90%

Shop 19.10%

Education 19.60%

Accompany child 0.60%

Other 10.30%

D2.3


Appendix D.

Comfort data – based on mobility and safety data

110

Appendix D. Comfort data – based on mobility and safety data

Comfort of cyclist based on mobility and safety data

Netherlands year

injured cyclists 2008 7 399 all injured person

killed cyclists 2008 145 7544

inhabitants 2008 16 500 000

injured cyclists per inhabitant 2008 0.000448424

killed cyclists per inhabitant 2008 8.78788E-06

modal share 2007 26%

average trips per day 2006 3.1

days a year 2006 365

trips per person per year with bike 2006-2008 294.19

total trips per year with bike in NL 2006-2008 4 854 135 000 average trips till a person will be injured or killed

average trips till an accident with injured P

2006-2008 656 053

average trips till an accident with killed P 2006-2008 33 476 793 643 443

Germany year









trips per person per year with bike 2008 128.1

total trips per year with bike in DE 2008 10 504 456 200 average trips till a person will be injured or killed

average trips till an accident with injured P 2008 133 023

average trips till an accident with killed P 2008 23 036 088 132 260

D2.3


Appendix D.


111

United Kingdom year


killed cyclists 2008 117 16 506




modal share 2008 2%



trips per person per year with bike 2008 19.8372

total trips per year with bike in UK 2008 1 229 906 400 average trips till a person will be injured or killed


2008 75 045


Estonia year

injured cyclists 2008 139 all injured person





modal share 2012 4%

average trips per day ??? 3

days a year ??? 365

trips per person per year with bike 2008-2012 42.705

total trips per year with bike in EE 2008-2012 57 224 700 average trips till a person will be injured or killed


2008-2012 411 688


D2.3


Appendix D.


112

Comfort of pedestrians based on mobility and safety data

Netherlands year

injured pedestrian 2008 1 499 all injured person

killed pedestrian 2008 56 1555


injured pedestrian per inhabitant 2008 9.08485E-05

killed pedestrian per inhabitant 2008 3.39394E-06




pedestrian trips per person per year 2006-2008 214.985

total pedestrian trips per year in NL 2006-2008 3 547 252 500 average trips till a person will be injured or killed

average trips till an accident with injured P 2006-2008 2 366 413

average trips till an accident with killed P 2006-2008 63 343 795 2 281 191

Germany year




injured pedestrian per inhabitant 2008 0.000399624





pedestrian trips per person per year 2008 294.63

total pedstrian trips per year in DE 2008 24 160 249 260 average trips till a person will be injured or killed


2008 737 267


D2.3


Appendix D.


113

United Kingdom year









pedestrian trips per person per year 2008 218.2092

total pedstrian trips per year in UK 2008 13 528 970 400 average trips till a person will be injured or killed



Estonia year

injured pedestrian 2008 468 all injured person







days a year ??? 365

pedestrian trips per person per year 2008-2012 214.62

total pedstrian trips per year in EE 2008-2012 287 590 800 average trips till a person will be injured or killed


2008-2012 614 510


D2.3


Appendix D.


114

Comfort of PTWs based on mobility and safety data

Netherlands year

injured motor-cyclists 2008 7 209 all injured person

killed motor-cyclists 2008 118 7327


injured motor-cyclists per inhabitant 2008 0.000436909

killed motor-cyclists per inhabitant 2008 7.15152E-06

modal share 2007 2%



trips per person per year with motor-bike 2006-2008 21.4985

total trips per year with motor-bike in NL 2006-2008 354 725 250 average trips till a person will be injured or killed

average trips till an accident with injured P 2006-2008 49 206


Germany year






modal share 2008 2%



trips per person per year with motor-bike 2008 24.339

total trips per year with motor-bike in DE 2008 1 995 846 678 average trips till a person will be injured or killed


2008 38 321


D2.3


Appendix D.


115

United Kingdom year






modal share 2008 2%



trips per person per year with motor-bike 2008 18.84534

total trips per year with motor-bike in UK 2008 1 168 411 080 average trips till a person will be injured or killed



Estonia year

injured motor-cyclists 2008 224 all injured person





modal share 2012 2%


days a year ??? 365

trips per person per year with motor-bike 2008-2012 20.805

total trips per year with motor-bike in EE 2008-2012 27 878 700 average trips till a person will be injured or killed


2008-2012 124 458
