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Commuters' enroute diversion and return decisions: Analysis and implications for advanced traveler information systems

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  • Khattak, Asad J.
  • Schofer, Joseph L.
  • Koppelman, Frank S.

Abstract

Incident-induced congestion is a major source of delay and frustration for drivers in large urban areas. Advanced Traveler Information Systems (ATIS) have been proposed within the framework of Intelligent Vehicle Highway Systems (IVHS) to address one component of the incident-induced congestion problem: diversion of drivers to alternate routes. To fully utilize the potential of ATIS, transportation managers need to understand driver response to such congestion. This study examines short-term commuter response to unexpected (incident-induced) congestion. It investigates factors which influence diversion from the regular route and return to the regular route after diversion. Discrete choice models of diversion and return behavior show that the following information and trip factors increase the probability of diversion: delay information received from radio traffic reports as opposed to observation of congestion, longer delays and longer travel times, and number of alternate routes used in the past. Further, drivers were more likely to divert if they lived in the city as opposed to the suburbs, were risk seekers, had a higher stated propensity to divert and were male. However, anticipated congestion on the alternate route inhibited drivers from diverting. Finally, drivers who had longer commute trips were more likely to return to their regular route. The most important implication for designing ATIS is that traffic information must be "customized" to account for individual differences. Specific design implications are discussed in this paper.

Suggested Citation

  • Khattak, Asad J. & Schofer, Joseph L. & Koppelman, Frank S., 1993. "Commuters' enroute diversion and return decisions: Analysis and implications for advanced traveler information systems," Transportation Research Part A: Policy and Practice, Elsevier, vol. 27(2), pages 101-111, April.
  • Handle: RePEc:eee:transa:v:27:y:1993:i:2:p:101-111
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    Cited by:

    1. Kucharski, Rafał & Gentile, Guido, 2019. "Simulation of rerouting phenomena in Dynamic Traffic Assignment with the Information Comply Model," Transportation Research Part B: Methodological, Elsevier, vol. 126(C), pages 414-441.
    2. Hamid Mostofi, 2021. "The Association between ICT-Based Mobility Services and Sustainable Mobility Behaviors of New Yorkers," Energies, MDPI, vol. 14(11), pages 1-18, May.
    3. Zhang, Michael & Shen, Wei & Nie, Yu & Ma, Jingtao, 2008. "Integrated Construction Zone Traffic Management," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt1bd50918, Institute of Transportation Studies, UC Berkeley.
    4. Lei Zhang & David Levinson, 2006. "Determinants of Route Choice and the Value of Traveler Information," Working Papers 200808, University of Minnesota: Nexus Research Group.
    5. Sophie Dantan & Julie Bulteau & Isabelle Nicolaï, 2015. "Hurried or Risk-adverse Travelers: who will Pay More for Multimodal Information?," Post-Print hal-04362230, HAL.
    6. Khattak, Asad & Kanafani, Adib & Le Colletter, Emmanuel, 1994. "Stated And Reported Route Diversion Behavior: Implications On The Benefits Of ATIS," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt4fz4h20k, Institute of Transportation Studies, UC Berkeley.
    7. Cristina Pronello & Amandine Duboz & Valentina Rappazzo, 2017. "Towards Smarter Urban Mobility: Willingness to Pay for an Advanced Traveller Information System in Lyon," Sustainability, MDPI, vol. 9(10), pages 1-21, September.
    8. Adler, Jeffrey L. & McNally, Michael G., 1993. "In-Laboratory Experiments to Investigate Driver Behavior under Advanced Traveler Information Systems (ATIS)," University of California Transportation Center, Working Papers qt81x1384q, University of California Transportation Center.
    9. Chen, Ting-Yu & Chang, Hsin-Li & Tzeng, Gwo-Hshiung, 2001. "Using a weight-assessing model to identify route choice criteria and information effects," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(3), pages 197-224, March.
    10. Richard H. M. Emmerink & Paul van Beek, 1997. "Empirical Analysis of Work Schedule Flexibility: Implications for Road Pricing and Driver Information Systems," Urban Studies, Urban Studies Journal Limited, vol. 34(2), pages 217-234, February.
    11. Caspar Chorus & Theo Arentze & Harry Timmermans, 2007. "Information impact on quality of multimodal travel choices: conceptualizations and empirical analyses," Transportation, Springer, vol. 34(6), pages 625-645, November.
    12. Franco Basso & Pedro Maldonado & Raúl Pezoa & Nicolás Szoloch & Mauricio Varas, 2022. "The Impact of Flashing on the Efficacy of Variable Message Signs: A Vehicle-by-Vehicle Approach," Sustainability, MDPI, vol. 14(15), pages 1-14, August.
    13. Motamed, Moggan & Machemehl, Randy B., 2013. "Traveler Path Choice During Freeway Closure," 54th Annual Transportation Research Forum, Annapolis, Maryland, March 21-23, 2013 206956, Transportation Research Forum.
    14. Richard H. M. Emmerink & Peter Nijkamp & Piet Rietveld & Jos N. Van Ommeren & Richard H. M. Emmerink & Peter Nijkamp & Piet Rietveld & Jos N. Van Ommeren, 2004. "Variable Message Signs and Radio Traffic Information: An Integrated Empirical Analysis of Drivers’ Route Choice Behaviour," Chapters, in: Location, Travel and Information Technology, chapter 16, pages 343-361, Edward Elgar Publishing.
    15. Hongcheng Gan & Xin Ye, 2013. "Investigation of drivers' diversion responses to urban freeway variable message signs displaying freeway and local street travel times," Transportation Planning and Technology, Taylor & Francis Journals, vol. 36(8), pages 651-668, December.
    16. Thill, Jean-Claude & Rogova, Galina & Yan, Jun, 2004. "Evaluating Benefits And Costs Of Intelligent Transportation Systems Elements From A Planning Perspective," Research in Transportation Economics, Elsevier, vol. 8(1), pages 571-603, January.
    17. Chorus, Caspar G. & Arentze, Theo A. & Molin, Eric J.E. & Timmermans, Harry J.P. & Van Wee, Bert, 2006. "The value of travel information: Decision strategy-specific conceptualizations and numerical examples," Transportation Research Part B: Methodological, Elsevier, vol. 40(6), pages 504-519, July.
    18. Sophie Dantan & Julie Bulteau & Isabelle Nicolaï, 2015. "Potential demand for multimodal information. Evidence from the Plateau-de-Saclay," Post-Print hal-01799290, HAL.
    19. Jou, Rong-Chang & Lam, Soi-Hoi & Liu, Yu-Hsin & Chen, Ke-Hong, 2005. "Route switching behavior on freeways with the provision of different types of real-time traffic information," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(5), pages 445-461, June.
    20. Casper G. Chorus & Harry J.P. Timmermans, 2011. "Personal Intelligent Travel Assistants," Chapters, in: André de Palma & Robin Lindsey & Emile Quinet & Roger Vickerman (ed.), A Handbook of Transport Economics, chapter 25, Edward Elgar Publishing.
    21. Khattak, Asad J. & Targa, Felipe & Yim, Youngbin, 2003. "Investigation of Traveler Information and Related Travel Behavior in the San Francisco Bay Area," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt4bx077j9, Institute of Transportation Studies, UC Berkeley.

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