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TRANSFORMING G2C/C2G RELATIONS THROUGH VIRTUAL
COLLABORATION: an E-Government Application in Transportation
Service
Sayuri Egaravanda*, Lukito Edi Nugroho*, Teguh Bharata Adji*, Ahmad Munawar**
* Electrical Engineering and Information Technology Department,
** Civil and Environmental Engineering Department,
Faculty of Engineering, Gadjah Mada University,
Jl. Grafika No. 2 Kampus UGM, Yogyakarta 55581,
Email: [email protected], [email protected], [email protected], [email protected]
ABSTRACT
This paper proposes a collaboration model among
user, government and transportation services. User
involvement is put into focus and gain more significant
role in decision making in transport management. This is
done by transforming information processing carried in a
Traveler Information System (TIS) system operated by
government. We develop Smart-ATIS, ATIS with two-
way communication system that allows user feedback for
more effective and efficient traffic management. In the e-
government framework, Smart-ATIS opens up
opportunities of citizen participation in urban
transportation management.
Keywords: Transformational System, Virtual
Collaboration, E-Government, Intelligent Transport
System, Advanced Traveler Information System, Smart-
ATIS.
1 INTRODUCTION
In the era of technological advancement, numerous
new information and communication technologies (ICTs)
innovation has been introduced to the public sector [1].
An important phase of e-Government implementation is
the transformation of government and government
organizations to provide better services. E-Government
era implies fundamental knowledge redistribution and
requires a careful rethinking of the management of
information resources and knowledge bases [2]. Within
e-Government, the focus of managing information
resources is predominantly on the management of
interactions among the government, citizens or business
[21].
In the transportation area, the concept of Intelligent
Transportation System (ITS) grows out of the need to
enhance the efficiency and safety of the current
transportation system. [5,6,7,8]. Typically ITS solution
involves three major functions: Monitoring, Automated
Analysis and Action. Based on analysis, ITS allows us to
make many changes that affect real transportation
services, for example: changing of traffic signal timing,
posting a message to overhead changeable message signs,
modifying transit schedules and rerouting buses,
dispatching emergency services, providing information to
the media and public electronically, plowing and salting a
roadway [9].
Providing information in transportation area is not
enough, it is imperative that this delivery satisfies
customers of government services [24]. In order to
provide various service levels and to meet rising
expectations, government needs to utilize recent
advances in technological development [23]. In the near
future, technology will permeate almost every business
practice. By embedding microprocessors and sensors in
materials and physical devices, Organizations will also be
able to create objects that respond to their internal or
external environment [4].
The services not only have the function as an
information provider but also indirectly increase the user
involvement of public services. User satisfaction can be
achieved by providing opportunities for user involvement
related to traffic management decision-making, in this
case illustrated by Area Traffic Control System (ATCS).
ATCS is the system that focuses on traffic signals, ramp
metering, and the dynamic message signs. Generally,
traffic light settings depend on traffic counting and traffic
surveillance. Providing information based on real time
condition, occasionally not suitable with the real
condition when traveler passed that intersection, because
of the differences time. This paper tries to describe the
new model which enables intervention of ATCS by
processing user information.
In this paper we propose a model in which improve
collaboration among user and government in
transportation services. The idea is to inject an
intervention to the system that creates a communication
channel for common users to participate in the traffic
management system (represented by ATCS), which in
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turn improves better decision making in traffic
management and information provision for users.
2 RELATED RESEARCH
ITS is a state-of-the-art approach based on
information, communication and satellite technologies in
mitigating traffic congestion, enhancing safety, and
improving quality of environment [3] and is mandatory to
provide access based on human spontaneous
communication ability [15].
In the early days of ITS deployment, Advanced
Traveler Information System (ATIS) was used to provide
basic information for travelers (e.g., routes). ATIS is an
integral component of ITS. It carries out data collection,
aggregation and processing, communications and
operates with traveler interface devices to improve both
of safety and efficiency of existing transportation system
[10]. ATIS delivers data directly to travelers or citizens,
empowers them to make better choices about alternate
routes or modes of transportation. Researchers classified
articles into 5 classes of ATIS’s, These Five categories
were: In-Vehicle Routing and Navigation Systems, In-
Vehicle Motorist Services Information Systems, In-
Vehicle Safety Advisory and Warning Systems, In-
Vehicle Signing Information Systems and Commercial
Vehicle Operations specific Funtions[9].
The important aspects of information are the content
and the type of information. Information in ATIS can be
categorized as (a) historical, real-time, or predictive, (b)
qualitative and quantitative, and (c) accurate, timely,
relevant, and reliable. Huang et al further investigated
from their view point of evaluation; the ATIS’s affects in
saving driver’s travel times and the travelers dynamic
responses, like purchasing the ATIS services and
believing the ATIS advice. According to J.L Adler,
model of Intelligent Traveller Information System
provides ITIS in which artificial intelligence techniques
Involvement of users in current ATIS improves their
confidence in using freeways and it is not only an
effective method of information presentation but also
allows more efficient navigation and less off-route, lost
time, and driver exposure [8]. Several models for
estimating link travel times on basis of individual data
sources (i.e. detectors, probe vehicles and driver reports)
was implemented to anticipate the problem based on
current conditions [14]. Users are generally appreciative
of traffic information that gives them a choice to make
decisions regarding their travel behavior as long as they
perceive the information to be accurate, timely and in-
expensive [11].
3 THE PROPOSED MODEL : SMART-
ATIS
3.1 The role of ATIS
Some information which are required by travelers are:
the current state of the network based on real-time
information across all transports modes, where
congestion exist and any particular conditions (such as
weather or incidents) and travel option.
Yurdaer, R., et.al, states that ATIS plays an important
role because the quality of the defined routes has an in-
depth impact on the performance of whole transport
system. ATIS highlights existing conditions on our
transportation system that we act on. It also highlights
historical patterns used for planning the system and leads
to travel choices for the traveler. Advanced Traveler
information involves the traveler into the decision
process [16].
Actually, the impact of ATIS in traffic pattern and
network performance is controversial for several reasons
[18]:
1. Even if all users had a perfect knowledge of the travel
cost associated to each available path and user
equilibrium was achieved, this could be very far from
an optimum configuration of the whole network in
terms of total cost sustained by all users;
2. Even if we find how to distribute traffic on the
different paths and over time in order to minimize the
total network cost, and provide the appropriate
information what will the driver reactions be to our
suggestions?
3. How will the proportion of equipped and not equipped
drivers with ATIS impact the network performance?
4. An overreaction can occur if too many drivers respond
to the information.
The new model will provide information in the
context of transportation system that requiring
correspondence between user expectation and the
information. Virtual collaboration explains interaction
among government, citizen and government services
(ATIS). Advanced technology will assist to get
information about users need and process with analytical
tools. Analytical tool associated with data modeling and
predictive analytics.
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3.2 Virtual Collaboration in Advanced
Traveler Information System
The essence of virtual collaboration is to break up the
unity of time, location and trade using information and
communication technology application.
In our model of ATIS we identify three typologies of
collaboration: government rules, context of system, and
user needs. Government rules are related to list of
activities, context of system is related processing process
and user needs is related output of ATIS (Table. 1).
Transformation process in government also relates to
collaboration between stakeholders. The idea of
collaboration corresponds with the concept of an
organization which includes collectiveness. It is obvious
that these collaboration instances have some benefits:
saves time or money, increases quality, innovating or
provides decision support ease of access to experts on
subject matter [13].
Table 1 ATIS as Information Service Provider
N
o Activities
Information
Processing Output
1
Collect, process,
store, and
dessiminate
transportation
information
Provide General
data warehouse
function
Collecting
information from
transportation
system operator
Route Choice
Prediction of
travel time, etc
2
2
Deliver of
traveler
information to
citizen
Provide realtime
traffic condition
Transit schedule
information
Ride maching
information
Parking
Information
Route
Guidance
Multimodal
Choice in
Trip Planning
Parking area
and capacity
Figure 1. Collaboration Environment
Fig. 1 illustrated common interaction between Traffic
Management System which represents Government (c),
Advanced Traveler Information System (ATIS)
representing Government product (a) and User (b).
Each component possesses a relevant description of
subject (ATIS), task (activities of ATIS), owner
(government) and output (information service of ATIS).
In existing model of ATIS, every component has its
own specific purpose in collaboration. Intersections
between sets illustrate that collaboration occurs. ATIS
(a) will interact with government, represented by ATCS
(c) in process of presenting related information about
route selection and guidance. c serves as a source of data
for a in describing existing traffic condition, based on
output of information processing in ATCS. a can give b
(users) an advice about path selection, related paths, and
estimated travel time through web based application
interfaces. b can then use the information to decide his or
her trips.
Our proposed model transforms the interactions
among a, b, and c. Intervention of advanced technology
(x) in the processing information will lead to changes the
business process. The intervention will be conducted by
addicting the function of a (ATIS), not only as an
information provider, but also as intelligent tool.
Figure 2 illustrates the establishment of a new model
of virtual collaboration. In our model, a, b, and c
intersect each other by means of advanced technology
intervention (x). Variable x identified as transformational
process in processing information caused by advanced
technology.
Figure 2. Future Collaboration Environment
The transformation produces two types of output,
route guidance and route prediction, without changing the
interacting participants. x will contains set of new rule in
processing information.
Future COLLABORATION
x COLLABORATION ENVIRONTMENT
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Variable x is the application that is associated with
advanced technologies and this application can be
adaptive to the current context and the user context. The
applications have tools to acquiring and representing the
current context (location, traffic conditions, and thus
sensors sometimes needed. Also, the application needs to
acquire and represent the next condition in path network
to get additional inputs in order to facilitating the new
scenario in managing of traffic system. The application
has value added that become autonomous and proactive
which can free users from initiating processes and tuning
them to suit the current context and current interest. In
this system x also has a function as analytical tools.
The next parts of this paper describes the detail of the
proposed model of ATIS, providing travel time
prediction and route choices and also process the
information with analytical tool, in order to predict traffic
condition. The result of forecasting information will be
handed over to ATCS for further decision on the timing
of traffic lights. The new scenario will causes a change in
Traffic Management System autonomously.
Future model experiencing transformation model in
processing information which allow the process of
collaboration between user (community), government
application (ATIS) and Government services (Traffic
Management System ) to describe the process of creating
a virtual communities supported by advanced technology.
The proposed model is Smart-ATIS.
3.3 Framework of SmartATIS with Dual
Engine
Smart-ATIS uses Dual Engine, Route Selection
Engine (RSE) and Route Prediction Engine (RPE). RSE
is working together with ATIS to provide optimum route
alternatives for traveler. RPE provides traffic forecasting
based on routes accepted by the traveler, determine
where traffic congestion will occur, and then sends the
intervention message to ATCS for pre-emptive
countermeasures.
Figure 4 explained conceptual framework of Smart-
ATIS. When traveler accesses route selection in Smart
ATIS, (1) RSE will calculate several optimum routes (a
route is composed of several path) based on current
traffic information available from ATCS data sources),
then presented back to the traveler (step 2). If traveler
accepts one of the recommended routes (step 3), RSE
will store and accumulate paths in storage. This storage is
part of RSE. Each path has a lifetime, only stored during
a definite period of time; this is called an active path.
Each route has estimated travel time (step 4); this will be
the path's lifetime. The collection of active path is then
processed by RPE (step5).
Figure 4. Framework of Smart-ATIS with dual Engine
RPE continuously performs forecasting based on the
collection of active path from the storage. During
forecasting, each path would have a new information
attribute, which is the future estimation of traffic load
(named “future traffic load”). This information then
compared to the threshold value indicating the maximum
traffic load on each path. If a path's future traffic load is
beyond threshold value, then a path can be determined as
congested (this attribute is named “future traffic state”).
Future traffic state value can be “congested” or “normal”.
The output of forecasting is a collection of path along
with the future traffic state attribute, transferred to ATCS
(step 6,7,8). Based on this feedback information, ATCS
can adjust the duration of traffic light on each path
according to the value of future traffic state in attempt to
achieve an optimal traffic flow state.
3.4 Implementation Architecture
We have so far discussed business process of
Smart-ATIS as a new paradigm in processing
information. To further understand the transformation
model of Smart-ATIS, it is helpful to view a Smart-ATIS
as special case and implemented in the real condition. In
order to acquire Smart-ATIS intervention, a pilot testing
should be done to districts/municipalities which already
have implemented ATIS and ATCS, for example
Jogjakarta Special Region. Existing ATCS in Jogjakarta
operates based on input from traffic surveillance and
traffic counting sensors.
Existing ATIS in Jogjakarta mainly provides
shortest route selection without considering real time
traffic conditions. Therefore, the existing ATIS needs to
be enhanced with a Route Prediction Engine which will
3 4
8
5
7 6
ATIS Route Selection Engine (RSE)
Forecasting
Route Prediction Engine (RPE)
ATCS
Accumulation
of active path
Real-time
accumulation of all
active path
1
2
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capture user preferred route selections, provide traffic
load forecasting on preferred routes, and then handover
the forecasting information to ATCS for further decision
on the timing of traffic lights. (Fig. 5).
Our proposed model illustrated a collaboration model
in government application in transportation represented
transformation process while a (ATIS), b (user),and c
(ATCS) affected each other. Intervention of advanced
technology (x) as analytical tool in the processing
information will lead to changes ATCS automatically.
3.5 Implementation Architecture
4 CONCLUSION
We have discussed transformational of existing
services to create virtual collaborations among
government-operated system (ATCS), transportation
services (ATIS) and users. Smart-ATIS allows
government to provide traffic information which suits
user needs, based on real-time traffic condition. At the
same time, the system also allows users to give feedback
to the ATCS system to be used for optimizing traffic
management in a specific area. In our future research, we
will develop traffic light simulation that models the
mechanism of Smart-ATIS.
REFERENCE
[1] Maria, A.Wimmer, Codognone,C., Xiofeng, Ma,
“Developing an E-Government Research Roadmap:
Method and Example from E-Govt, RTD, 2007.
[2] T.C. Hsia, “Simple Robust Schemes for Space
Control of Robot Manipulators”, Int’l. J. of Robotics
and Automation, 9(4), 1994, 167- 174.
[3] http://www.accenture.com/xd/xd.asp?it=enweb&xd=i
ndustries\government\gove_thought.xml
[4] Rivard, S., Aubert, A. Benoit., Patry, M., Pare,
G.Smith, A, Heather,” Information Technology and
Organizational Transformation”, Elsevier, 2004.
[5] Cheslow, M., Hatcher, S., and H sin V. J.,
"Communication, Storage, and Processing Load
Requirements of Alternative Intelligent Vehicle
Highway Systems Architectures”, MITRE, 1993.
[6] Cheslow, M., Hatcher, S.,Mc Gurrin, and M. Mertig,
A., "Alternative IVHS Architectures", MITRE, April
1992.
ATIS
ADVANCED TRAVELER
INFORMATION SYSTEM
Improving the performance of
transportation networks and
Quality of Travel
1. assist traveler in making
pre trip
2. enroute travel choices
decision
1.Depature time
2. route
3.travel mode
4. cost
5. travel time
6. Destination
Information processing
Implement structural mechanism
and data processing capability to
enhance the dataflow (reduce
uncertainty)
Decision to
aquire
information
Constrain:
Time,effect,money,
modes
Benefit:
Potential to help make
right choices given
applied strategy
Trip context:
Complexity of the
choices situation,
time presure
Information Service:
Availability, price,
ease of use,
reliability,relevance,
resourcefullness
1.Traveler Knowledge
2.Decision strategy
1. Alternative
2. Availibility
3. Potential
atractiveness
Understand travel challenge
What information traveler needs and wants
Which information would be presented to the traveler
Where the traveler would want the information presented
Communications and traveler
interface devices
OPERATIONAL DATA
Route Selection Planning
ANALYTICAL TOOLS
(INTELLEGENCE
ANALYSIS)
Raoute Prediction palnning
Ge
ne
rate
ACTION
POINT
Autonomous Traffic
Management
System
Data
Sources
ATCS
USER NEEDS
USER
INTERVENTION
Figure 5 .Implementation Model of Smart-ATIS
5-07 Transforming G2c/c2g Relations Through Virtual Collaboration: An E-government Application In Transportation Service
151
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[7] Cheslow, M., Hatcher, G., and Patel V., "An initial
Evaluation of Alternative Intelligent Vehicle Highway
Systems Architectures", MITRE, April 1992.
[8] Yurdaer N. Doganata, Denos C. Gazis, and Asser N.
Tantawi, “A communication Network Architecture
for Transportation Information System”, IBM
Research Division, 1995.
[9] Anonymous, “Intelligent Infrastructure: Delivering
the Competitiveness Benefits an Enterprise
Opportunities, Fortas Publication, 2011.
[10] David Levinson, “The Value of advanced traveler
information system for route choice”, Transportation
Research Part C11, 2003 pp. 75-79
[11] Noonan, J. Shearer,O., “ Intelligent Transportation
System Fields Operational Test Cross-Cutting Study
Advance Traveler Information System, Booz Allen &
Hamilton Inc, 2008.
[12] Zigurs,I. and Buckland, B. K., “A Theory of
Task/Technology Fit and Group Support Systems
Effectiveness,” MIS Quarterly (22:3), 1998, 313-
334.
[13] Coleman D., Levine S., "Collaboration 2.0:
Technology and best practices for successful
collaboration in a web 2.0 world", ISBN 160005-
071-9, California, USA, 2008.
[14] H.Bruce and Gudapati, R., “Estimating link Travel
times for advanced Traveller Information Systems”,
University of Waterloo, Canada, 2000.
[15] Petriu, E.M., Patry G, Whalen, T.E., Al-dhaher, A,
Groza, V.Z., “Intelligent robotic sensor agents for
environment monitoring”, Visms 2002 int Symp on
Virtual and Intelligent Measurement System, 18-20
May 2002.
[16] J. C. Q. Dias, J. M. F. Calado, A. L. Osório and L. F.
Morgado, "Intelligent Transport System Based on
RFID and Multi-Agent Approaches", International
Federation for Information Processing, Volume 283,
Pervasive collaborative Networks, (Boston:
Springer), 2008, pp. 533–540.
[17] Singh,V., Kumar, P., “Web based ATIS for
Developing Countries”, Journal of Transportation
Engineering, 2010.
[18] D.Buscema, M. Ignaccolo, G. Inturri, A. Pluchino,
A. Rapisarda, C. Santoro, and S. Tudisco, “The
impact of real time information on transport network
routing through intelligent agent-based simulation,”
in Science and Technology for Humanity (TIC-
STH), IEEE Toronto International Conference,
Sept, 2009, pp. 72–77
[19] J.L. Adler, Victor, J. Blue, “Toward the design of
Intelligent traveler information systems”,
Transportation Research Part C, Vol 6, June 2006.
[20] Hai-Jun Huang, William, H, K, Lam, “A Multi-Class
Dynamic User Equilibrium Model for Queuing
Networks with Advanced Traveler Information
Systems”, Journal of Mathematical Modeling and
Algorithms, 12-2003, Vol.2, pp 349-377.
[21] Wagner,C., Cheung,K., Lee,F., Rachael IP.,
“Enhancing E-government in Developing Countries:
Managing Knowledge Through Virtual
Communities”, The Electronic Journal of
Developing Countries, 2003.
[22] W.Eric,W., H.Charles,C., “Internet use, transparency
and interactivity effects on trust in Government,
Proceedings of the 36th Annual Hawaii
International Conference on System Sciences, 2003.
[23] T.A Horan, T.A Raghiuvira, “Assessing user
satisfaction of E-Government Services:
Development and testing of quality-in-use
satisfaction with Advanced Traveler Information
System (ATIS)”, Proceeding of the 39th Hawaii
International Conference on System Sciences, 2006.
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