AN INTEGRATED PEDESTRIAN AND VEHICLE INTERFACE MODELLING TOOL FOR EFFICIENT PLANNING OF SHARED SPACE

Samya Ghosh,Regional Director-AECOM, UK

Rekel Ahmed Consultant-AECOM, UK

1. INTRODUCTION

Shared space is an urban design approach that aims to minimise the segregation between vehicles and pedestrians through the removal of traditional street elements such as traffic lights, pedestrian markers and kerbs. Shared space is more than just a design concept; it is about reclaiming the public realm from the dominance of the car and achieving a better balance between the street’s movement and social roles, and rebalance the share of urban network utilisation between pedestrians and vehicles.

The concept has developed most in countries like Denmark, Northern Holland, Sweden and Northern Spain and is now also being employed much more in the UK. It was found that accidents have decreased by 41% at Britain’s first shared space in Ashford, Kent. In addition to this, the Mayor of London has made commitments to high quality urban design across the Greater London Authority (GLA) and TfL. This growing desire for effective urban planning and creating urban areas that embrace concepts such as shared space has led us to investigate what tools, modelling applications, analysis techniques and advisory guidance are currently available to assist in efficient and effective planning of urban spaces. These are detailed in the following section.

2. AN OVERVIEW OF THE SHARED SPACE CONCEPT

Different shared space schemes have different specific objectives. However, virtually all schemes are based on the theory that removing the boundaries between pedestrians and cars creates a more pedestrian-friendly environment whilst also encouraging free-flowing traffic as vehicles move slower along shared road spaces. The main objectives of shared space policies are listed below:

Smoothing traffic flows at major junctions. Such policies are widespread in mainland Europe. When these schemes are active along road-spaces, drivers become more cautious of oncoming pedestrians and reduce their speed, causing a subsequent reduction in stop-and-go behaviour and improving the flow of traffic. This reduces congestion in major junctions, as well as having a number of environmental benefits with vehicles consuming significantly less fuel.

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Allowing pedestrians to move more freely within space at minor junctions (DfT, 2011). This is the focus of shared space policies in the UK. By removing barriers and ‘controlled’ junctions; pedestrians are able to follow their desired path, rather than following the building line across streets.

Improving the ambience of places (Moody and Melia, 2014) by reducing clutter such as road signs and traffic lights, and replacing them with lines of trees and adding uniform level surfaces.

Improving the quality of public realm. Good public realm planning promotes health and wellbeing amongst the people who use these facilities, increases the quality of the physical environment and promotes the social aspect of the environment (Besley, 2010). Good public realm planning involves implementing policies which actively benefit people who use the public streets; such as the widening of pavements to accommodate more people using the streets.

Besley (2010) identifies shared space as the most recent approach to ‘balance the seemingly conflicting mobility and civility aims of a place’. By removing boundaries between cars and pedestrians; cars are able to move at a steady pace (retaining mobility) whilst pedestrians are able to more easily follow their desired route (increasing mobility).

As the concept of shared space is becoming more popular and widely adopted, a need has arisen for a consistent guidance and analysis techniques that can be used for the design and evaluation of shared space areas. A few findings from some of the relevant guidance documents are summarised here.

2.1 Department for Transport (DfT, Govt of UK) Guidance Documents

In October 2011, the Department for Transport published Local Transport Note 1/11 which provides guidance on how shared space areas should be designed. The document considers the needs of all users including pedestrians, people with disabilities (mobility impaired, visually impaired, hearing impaired, cognitive impairment), cyclists and drivers and provides guidance on how the needs of all users should be considered when designing shared space areas. The document also outlines what design principles should be considered (de-cluttering, designing for low speeds, crossing design etc.) when designing public realm areas.

In October 2011, the Department of Transport published a report called “Designing the Future, Shared Space: Operational Assessment”. Through the use of an evidence based approach, this report provides an operational assessment of shared space schemes. The report notes that that there is currently limited research available into the operation of shared space schemes in the UK and aims to address knowledge gaps by collecting observational data of driver/pedestrian behaviour at sites across the UK. Analysis of the collected data (through regression analysis and analysis of desire lines for pedestrians), found that introducing shared space areas result in changes to pedestrian and driver behaviour. The analysis found that the

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more shared a site is, the more likely it is that pedestrians will use the entirety of the space and the more likely it is that pedestrians will use desire lines when crossing the carriageway as opposed to using more dedicated crossing points. It was also found that shared space areas resulted in lower vehicle speeds with mean speeds across the majority of the schemes analysed being 15mph or less despite the differences in the legal speed limit.

In addition to the above, the Department of Transport also published a report titled “Designing the Future, Shared Space: Qualitative Research”. The report describes qualitative research that has been undertaken in areas where shared space design has been implemented as part of a larger study. The research includes gathering information such as accompanied journey times and undertaking interviews with a number of different user types including drivers, pedestrians and pedestrians with disabilities (visually impaired, mobility impaired, deaf and those with learning difficulties). The main aims of the research was to gain an understanding of how drivers and pedestrians behave in the streets and understand how disabled persons orientate themselves and navigate in shared space.

2.2 Transport for London’s (TfL) Guidance Documents

TfL’s urban design team have also published a number of guidance documents relating to the public realm. In September 2013, TfL’s Urban Design Team in collaboration with Urban Design London published Better Streets Delivered. The document contains details of recently completed schemes that have been completed under London’s Great Outdoors and Better Streets programme and celebrates the ambition and success of recent public realm projects across London. The document categorises the projects into five sections:

Streets: Projects that identify opportunities to improve the quality of the space by compromising on road traffic.

Public Spaces: These spaces need to satisfy the demands and needs of a wide range of users.

Interchanges: This is an important part of efficient travel and form the link between different transport networks. As such, the success of these spaces is in their ability to provide an environment in which a variety of transport modes can run smoothly in parallel.

Junctions and Links: These schemes show how the contribution that good junction design can have on the wider public realm.

Town Centres: The success of town centres is not only dependant on the quantity, type and location of services but also on the diversity and character of the street.

These schemes show that the most successful projects respect the existing character of a place while providing strong and lasting measures that enhance the experience for those using the space. While this document outlines the different projects that are currently happening across London, it does not help designers and urban planners to effectively assess how different designs will perform or help to quantify the benefits of different schemes.

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More recently (2015), TfL’s Urban Design Team published the Royal Docks Local Transport Design Guidance in collaboration with the Greater London Authority and London Borough of Newham. The document outlines the shared aspiration to deliver improvements in the Royal Docks Opportunity Area by enhancing the place and movement functions of streets and spaces.

In addition to the above, TfL (in collaboration with Grimshaw Architects and BDP) have published the Station Public Realm Design Guidance in August 2015. This guidance sets out an agreed approach for how the space outside stations should be developed and designed to the benefit of the transport user, the community, commercial interests and place making in general.

2.3 Transport for London’s Valuing Urban Realm Toolkit (VURT)

In addition to all the urban realm guidance documents that have been published by TfL’s Urban Design Team, the team have also developed what is known as the Valuing Urban Realm Toolkit (VURT). This toolkit uses observed data to calculate the monetary benefit of investing in high-quality urban realm projects.

VURT uses PERS (Pedestrian Environment Review System) to assess both the quality of the existing streetscape and of the streetscape arising from the implementation of the proposed scheme or option. PERS has a seven point quality scale from -3 to +3 and covers two sets of attributes: link attributes and place attributes. Link attributes relate to the experience of moving through a street/space and include: effective width, dropped kerbs, obstructions, permeability, legibility, lighting, personal security, surface quality, user conflict, quality of environment and maintenance. Space attributes relate mainly to the experience of staying in a street/space and include: moving in the space, interpreting the space, personal safety, feeling comfortable, sense of place and opportunity for activity. Usually scores for both sets of attributes are assessed for a given scheme or option.

Based on this analysis, VURT produces two main outputs: Property Benefits (increases in residential prices and retail rents) and User Benefits (the values people say they give to changes in urban

realm quality.

User benefits are calculated according how many people experience the change in urban realm quality and for how long they experience this change. VURT uses the counts of pedestrians walking or staying in a street for a particular time period and then calculates the user benefit for that time period. Scaling factors are then applied to produce annualised user benefit value and total user benefit value up to a specified future year.

Property benefits are calculated through an assessment of the average residential property prices on the street and total rentable value of retail properties on the street. Percentage uplift is then applied to monetise the total

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increase in residential values and retail rentable values on the street for the base year. The property benefits over the lifetime of the scheme are then calculated.

Once the user benefits and property benefits of the scheme are calculated, VURT then calculates the benefits for the whole life of the scheme and then compares these benefits to the overall cost of the scheme over its lifetime and calculates a benefit to cost ratio which can then be used to provide objective justification for public realm investment.

The above discussion leads us to conclude that the standards and guidance on shared space planning are on their nascent stages of development. The analysis methods and techniques to inform and evaluate the shared space designs are also evolving.

3. SHARED SPACE ASSESSMENT TOOLS

Since the interactions between pedestrians/road users and shared space operation is not yet fully understood, the development of standardised and uniform modelling algorithms and tools attempting to replicate real-world conditions is still in its early infancy.

We discuss briefly in the following one emerging algorithm and one prevailing tool often used to inform and assess partially the shared space characteristics.

3.1 Social Force Algorithm

Anvari et al., (2014) used a variation of the computer Social Forces Model to produce feasible trajectories in mixed traffic environment. The Social Forces formulae attempts to emulate real world characteristics by applying a force which prevents cars colliding with other cars and pedestrians. The formula uses the shortest path direction which predicts the real-world direction that the car would be moving towards. It also adds a car-following feature which replicates the movement which car users show in shared space situations (Figure 1).

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Figure 1: Illustration of the forces applied to the car as it moves through the model

3.2 Space Syntax Network

Space syntax network is a tool that is often used to inform the shared space designs and undertake their assessment in terms of impact on circulation patterns. This tool investigates the relationship between spatial layout and a range of social, economic and environmental attributes (movement patterns, awareness and interaction, land use, urban growth, social differentiation/safety and crime distribution).

The tool was pioneered in the 1970s by Prof Bill Hillier, Prof Julienne Hanson and colleagues at The Bartlett, University College London. The models integrate a number of factors that influence behaviour including:

location of transport nodes; distribution of object attractors; land uses and spatial layout hierarchy, from more accessible to less accessible

places.

Space syntax models are able to simultaneously analyse vehicle, pedestrian and cycle networks, explain existing movement patterns and forecast future scenarios by demonstrating the relative influence of a number of key factors (spatial layout attraction, land use attraction and transport attraction). Figure 2 shows a sample output from a space syntax model.

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Figure 2: Space Syntax Output

The approach is to first transform the street network of an area or the room layout of a building into a network “graph”. The network is then broken down into “segments” (for street layouts) or “tiles” (in building layouts), which are then evaluated using a mathematical algorithm that calculates each segments or tiles inter-accessibility within the network (i.e. how easy it is to reach said segment/tile from all other segments/tiles in the network) or how likely it is that movements between different parts of the network pass through the segment/tile being analysed. In this way, the model calculates the “to” and “through” movement characteristics of each segment/tile, thereby calculating the accessibility and connectivity of the network.

The tool can be used for a number of commercial applications including town planning, connectivity and accessibility analysis and urban and architectonic analysis.

From the above discussion, it can be inferred that while the current thought process and the application of available tools can partially support in design and/or assessment of shared space, there is still a large gap to be filled in, mainly in terms of development and application of a tool which can iteratively determine the routeing and predicted flows of pedestrians (and other travel modes plying on the shared space) across available alternate routes. This capability is particularly important and relevant when the alternate locations of different landuse nodes and their associated network are being planned and evaluated to arrive at a preferred landuse/ network option. The intent is to develop a tool that can help in the planning of shared space by initially assessing the connectivity of the whole network and accessibility of the focal

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nodes and then go on further to determine the routeing of pedestrians and other vehicular modes likely to ply on the shared space; for different sets of landuse and network options; and predict the flows on various links and nodes robustly; to be able to identify the sections of the network which are under maximum stress and are likely to experience unacceptable levels of congestion or conflict—so that they can be planned and assessed and mitigated at a detailed and disaggregated level.

4. EVOLVING AECOM’s URBAN SPACE TOOL

Having identified the gap of a robust analytical tool, which can comprehensively support the emerging design options of shared spaces and also assess their quality and impact on circulation patterns and flow intensities successfully, AECOM’s Urban Space team has developed an in-house tool, named as “Urban Space” model, and has applied it in some ongoing studies to extract robust outputs and obtain valuable feedback, which are discussed in this paper.

4.1 Tool Development

The tool has been developed using a series of python scripts with graphical user interface. Python is a high-level, general purpose programming language which can be used as a scripting language for several software packages, including PTV Visum, PTV Vissim, PTV Viswalk, and ArcGIS. Python consists of a core language, and an extensive set of specialized libraries.

The scripts enable the user to store and manage different data layers relevant to pedestrian analysis, such as maps of pedestrian footpaths, vehicle carriageways, and the location of buildings and public transport stations. In addition, they can be used to calculate values for various indicators relevant to pedestrian planning, such as proximity to public transport stations and overall network connectivity. To do so, the scripts take advantage of the graphical user interfaces, network editing capabilities, and geoprocessing tools from software packages such as PTV Visum and ArcGIS, as well as Python libraries such as NetworkX (network analysis), Pandas (data analysis), Shapefile (reading and writing shapefiles in Python), and Matplotlib (plotting).

Figure 4 below describes the overall logic and the main components of this tool. The boxes shown in orange indicate components of the tool that are already finalised, whereas the boxes shown in grey and with a dotted contour line indicate components that have only been partly tested and which indicate future areas of development for this tool.

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Figure 3: Overview of the Modelling Approach

4.2 Urban Space Tool: Applications and Analysis Methodologies

The salient capabilities of the Urban Space tool are outlined below:

Public transport coverage analysis Catchment area analysis for public transport Walking distances to public transport stations along the pedestrian

footpath network

Connectivity and accessibility analysis Evaluation of area – wide network connectivity Assessment of the accessibility to retail, public spaces and parks Comprehensive maps of pedestrian and bicycle infrastructure

Pedestrian flow analysis Pedestrian flow maps by time of day and day of the week

Integration of pedestrian and vehicle models Mapping of traffic volumes and speeds by time of day, based on

outputs from traffic models Potential for developing additional indicators based on traffic model

data, such as pedestrian crash risk, exposure to air pollutants, etc.

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Neighbourhood level analysis to identify key areas for intervention to be modelled in detail using microsimulation software

The urban space tool estimates the “Accessibility” of the identified nodes by computing the walking distance in meters to the closest transport node of interest (e.g. rail station/bus station etc.). It then generates a “access” attribute and then computes the mean value of “access” value between two nodes. The urban space tool then allocates each edge to a category, based on the value of “access” with respect to certain thresholds (e.g. 150, 300, 600, 900, and 1200 meters), corresponding to specific walking times, based on an average pedestrian speed of 1m/s. It then generates a plot of the network, colour coding edges based on the value of ‘access’ and saves it in the working folder.

For connectivity analysis of the network, the following tasks are performed:For each node in the ‘sidewalk’ layer, computes a connectivity index and adds it as a node attribute named ‘access’; and then for each edge in the ‘sidewalk’ layer, generates an attribute named ‘access’ and assigns to it a value equal to the mean of the value of ‘access’ for its two nodes. Thereafter a a Matplotlib plot of the network is generated, colour coding edges based on the value of ‘access’ and the figure saved in the working folder.

For interfacing data from traffic models, the following approach is adopted: A Matplotlib plot of the network, with edges in the ‘streets’ layer colour coded based on overall traffic volumes for their corresponding links in the traffic model, and saves the image as a file named ‘Traffic.png’. Thereafter a Matplotlib plot of the network is generated, with edges in the ‘streets’ layer colour coded based on overall traffic speeds for their corresponding links in the traffic model, and saves the image in the working folder.

Based on the above analysis a whole set of outputs can be generated, iteratively with the design development process, in terms of:

- Accessibility of the nodes- Connectivity of the network- Pedestrian Flow data plots- Traffic Flow data plots- Traffic Speed data plots

5. APPLICATION AND CASE STUDIES

The tool has already been used by the Urban Space team of AECOM in a few projects and is continuing to be used in live projects. This section details the urban space tool’s application in some recent work.

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5.1 Traffic Modelling of an Urban Centre Regeneration Study, a London Borough

As part of a study in a borough of London, AECOM’s Urban Space tool was used to analyse the adequacy of pedestrian infrastructure and flows on the major streets in the area. Connectivity maps of the area were developed as well as public transport coverage maps, which together with pedestrian surveys, allowed us to analyse the spatial and temporal distribution of pedestrian flows in the area and understand their key drivers.

Figure 4 shows the spatial connectivity analysis map which analyses how attractive each street segment is for pedestrians, based on how easy it is to reach that street from the rest of the network. Streets shown in darker shades of red are better connected, which suggests that they will be likely to attract more pedestrians.

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Figure 4: Spatial Connectivity Analysis

The map in Figure 5 shows the bus network coverage of the area and evaluates walking distances to the nearest bus stop. The area is very well served by buses, with most streets within less than 10 minutes’ walk to the nearest stop. Figure 5 also shows the rail coverage map for the study area and evaluates walking distances to the nearest national rail and tramlink stations.

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Figure 5: Bus/Rail Accessibility Analysis

The tool has also be used to plot data from traffic micro-simulation models such as VISSIM. Figure 6 display the traffic volumes and traffic speeds that have been plotted for the AM peak period.

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Figure 6: Traffic Volumes and Traffic Speeds (AM Peak)

This tool has been used to calibrate the pedestrian flows of certain links of the study area by comparing with observed counts and then estimating the flows for rest of the links for which no data was available, thus saving on a lot of time and effort to offset the data gap.

The model will further be used to predict the pedestrian flows on various links of the study area, based on background growth as well as planned landuse growth and distribution in the study area.

5.2 Urban Space Tool Application: Masterplanning Design Competition, East London

AECOM have also used this tool for analysing the connectivity and accessibility of a prestigious large development in East London as part of a submission to a design competition. Using the urban space tool, the current pedestrian network was analysed in terms of connectivity. Figure 7 below shows the outputs of this analysis and demonstrates that there is some room for improvement (in terms of connectivity), both in the area around the focal

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node of the major venue/stadium and also in terms of connections to the broader urban context.

Figure 7: Connectivity Analysis for the Current Network

Figure 8 shows the connectivity map for a proposed future year network. This network has an extra link, which is demonstrated to improve connectivity within the overall network. Figure 9 shows the connectivity plot for the future year network proposed by AECOM. From this, it can be seen that the addition of a few more links and an additional bridge significantly increases the connectivity of the overall network.

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Figure 8: Connectivity Analysis for Future Network (Option 1)

Figure 9: Connectivity Analysis for Future Network (Option 2)

6. FUTURE DEVELOPMENTS16

A number of further developments are planned for the urban space tool. Currently the tool is in its development stage and a number of further developments are envisioned for the future. These include, but are not limited to:

Integrate the outputs of traffic model outputs into the tool so that this information can be used to further predict the vehicle/ pedestrian conflict and interface.

Combine pedestrian and vehicle flow data to highlight the “pinch points” in the network.

Create pedestrian route choice models. Create pedestrian crash risk models.

7. CONCLUSIONS

The concept of shared space is becoming more valued and widely used, both in the UK and abroad. However, an investigation into the current analysis methods and tools available to inform the design of shared space areas has shown that current research and analysis tools in this area are very limited.

The urban space tool aims to bridge this gap and develop an integrated tool that will be flexible to the needs of the user. When completed, the urban space tool will be able to not only assess accessibility and connectivity for pedestrians and predict route choice and intensity of flows for key attractor nodes and the links connecting those nodes, it will also be able to combine traffic flow data from traffic models comprehensively inform the design of a planned shared space by considering the needs of both pedestrians and vehicles.

8. BIBLIOGRAPHY

[1] Hillier, B.H. (2007) Space is the machine; A configurational theory of architecture[2] http://www.spacesyntax.net[3] Department of Transport, (2011), Local Transport Note 1/11 Shared Space[4] Transport for London and Urban Design London, (2013), Better Streets Delivered (Learning from Completed Schemes)[5] Transport for London, (2015), Royal Docks Local Transport Design Guidance Issue 01[6] Transport for London, (2015), Station Public Realm Design Guidance[7] Department of Transport, (2011), Designing the Future Shared Space: Operational Assessment[8] Department of Transport, (2011), Designing the Future Shared Space: Qualitative Research [9] Transport for London, (2015), Valuing Urban Realm Toolkit: User Guide for 2015 Basic v1.0

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