Evaluating Perceived Quality of Traffic Information System using Structural Equation Modeling

다국어 초록 (Multilingual Abstract)

Megacities worldwide have been employing some form of traffic information systems to manage their road network and to mitigate congestion. However, the full benefits of such systems can only be achieved if drivers perceive the system to be of adequate quality for them to actually use the disseminated information in their travel choices. One way to evaluate the underlying quality of the system is to conduct questionnaire survey, gather direct driver feedback and perform statistical analyses to derive attributes or indicators such as driver awareness, utilization of traffic information and perceived effectiveness which are useful to agencies for their planning and management activities. However many past works have treated the attributes to be independent and did not offer a complete picture on the perceived quality of the traffic information system. This paper therefore presents the development of a holistic structural equation model that can consider all potential attributes affecting perceived quality in a single framework.
Attributes considered in the paper include: driver awareness, driver utilization, perceived effectiveness, expectation, and perceived necessity of the system. Using the traffic information system in Klang Valley, Malaysia as a case study, it is demonstrated that there are causal and cross-loading relationships between the attributes contributing to perceived system quality and the attributes must be considered in a comprehensive manner. In addition, the model offers a useful interpretation on the factors affecting road user perception on the traffic information system, thereby allowing agencies to undertake appropriate measures to further improve the level of user satisfaction.

참고문헌 (Reference)

1 Simma, A., "Within-household allocation of travel: The case of upper Austria" 2001

2 Pierce, S., "Why don’t more people use advanced traveler information? Evidence from the Seattle area" 2004

3 Emmerink, R. H. M., "Variable message signs and radio traffic information: An integrated empirical analysis of drivers route choice behavior" 30 (30): 135-153, 1996

4 Abdel-Aty, M. A., "Using stated preference data for studying the effect of Advanced Traffic Information on drivers’ route choice" 5 (5): 39-50, 1997

5 Tsirimpa, A., "Travelers response to VMS in the Athens area" 179-187, 2009

6 Yim, Y., "Traveler response to new dynamic information sources: Analyzing corridor and area-wide behavioral surveys" 2002

7 Raub, R. A., "Towards a better understanding of needs for travel information: Analysis of a commuter survey" 2003

8 Hoyle, R. H., "The structural equation modeling approach: Basic concepts and fundamental issues, In Structural Equation Modeling: Concepts, Issues, and Applications" Sage Publications, Inc 1-15, 1995

9 Bonsall, P., "The influence of route guidance advice on route choice in urban networks" 19 (19): 1-23, 1992

10 Suhr, D., "The basics of structural equation modeling"

11 Spyridakis, J., "Surveying commuter behavior: Designing motorists information systems" 25 (25): 17-30, 1991

12 Zheng, X. -S., "Study on setting of VMS for urban expressway based on SP survey" City Hall Kuala Lumpur

13 Bollen, K. A., "Structural equations with latent variables" John Wiley & Sons 1989

14 Golob, T. F., "Structural equation modeling for travel behavior research" 37 (37): 1-25, 2003

15 Ng, L., "Statistical analysis of the impact of traveler advisory systems on driving behavior" 1999

16 Silvia, E. S. M., "Some factors affecting the success of specification searches in covariance structure modeling" 23 (23): 297-326, 1988

17 IBM Corporation, "SPSS Amos: Take your analysis to the next level and get your research noticed"

18 Jou, R-C., "Route switching behavior on freeways with the provision of different types of real-time traffic information" 39 (39): 445-461, 2005

19 Richards, A., "Questionnaire surveys to evaluate user response to variable message signs in an urban network" 1 (1): 177-185, 2007

20 Kline, R. B., "Principles and practice of structural equation modeling" The Guilford Press 1998

21 Peng, Z.-R., "Motorist response to arterial variable message signs" 2004

22 Yim, Y., "Link flow evaluation using loop detectors data: Traveler response to variable message signs" 1550 : 58-64, 1996

23 Golob, T. F., "Greenhouse gas emissions and Australian commuters’ attitudes and behavior concerning abatement policies and personal involvement" 3 : 1-18, 1998

24 Sutandi, A. C, "Evaluation of the impacts of VMS on traffic performance measures in an urban area in Indonesia" 10 (10): 28-34, 2008

25 MV2, "Evaluation of efficiency of variable message sign policy (in France), Report to Direction Regionale Authority" 1997

26 Lee, D., "Evaluation of driver satisfaction of travel information on variable message signs using fuzzy logic" 42 (42): 5-22, 2008

27 Chen, L. W., "Effects of changeable message sign display on the route choice behaviors of drivers on freeway" Feng Chia University 2007

28 Choocharukul, K, "Effects of attitudes, socioeconomic and travel characteristics on stated route diversion: A structural equation modeling approach of road users in Bangkok" 2048 : 35-42, 2008

29 Chen, S., "Effects of Variable Message Signs (VMS) for improving congestion" 416-419, 2008

30 Wardman, M., "Driver response to variable message signs: A stated preference investigation" 5 (5): 389-504, 1997

31 Morikawa, T., "Discrete choice models with latent variables using subjective data, In Travel Behavior Research: Updating the State of Pla" 435-455, 1998

32 Papageorgiou, M., "Control strategies for variable message signs" Artech House 1229-1236, 1994

33 Peeta, S., "Content of variable message signs and on-line driver behavior" 1725 : 102-108, 2000

34 Khattak, A. J., "Commuters’ enroute diversion and return decisions: Analysis and implications for advanced traveler information systems" 27 (27): 101-111, 1993

35 Tardiff, T. J., "Causal inferences involving transportation attitudes and behavior" 11 (11): 1-10, 1976

36 Messmer, A., "Automatic control methods applied to freeway network traffic" 30 (30): 691-702, 1994

37 Caplice, C., "Aspects of commuting behavior: Preferred arrival time, use of information and switching propensity" 26 (26): 409-418, 1992

38 MacCallum, R. C., "Applications of structural equation modeling in psychological research" 51 : 201-226, 2000

39 Fuji, S., "Anticipated travel time, information acquisition and actual experience: The case of the Hanshin expressway route closure" 1725 : 79-85, 2000

40 Xu, C., "Analyzing travelers’ intention to accept travel information: Structural equation modeling" 2156 : 93-100, 2010

41 Golob, T. F., "A vehicle usage forecasting model based on revealed and stated vehicle type choice and utilization data" 31 : 69-92, 1997

42 Kuppam, A. R., "A structural equation analysis of commuter activity and travel patterns" 28 (28): 33-54, 2001