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Capturing the interaction between travel time reliability and route choice behavior based on the generalized Bayesian traffic model

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  • Zhu, Zheng
  • Mardan, Atabak
  • Zhu, Shanjiang
  • Yang, Hai

Abstract

Travel time reliability plays an important role in travelers’ route choice behaviors. Based on a previously developed generalized Bayesian traffic model, we propose different types of perceived knowledge (i.e., mean-variance-based type, relative gap-based type, and penalty-based type) to model travelers’ daily route choice behavior concerning travel time reliability. We theoretically demonstrate the flexibility of the generalized Bayesian model in capturing various existing UE-based travel behaviors and other non-UE-based travel behaviors (e.g., penalty-based) in stochastic transportation systems. Three major conclusions are obtained. First, the route choice dynamics induced by the Bayesian model with an infinitely long memory and mean-variance-based perceived knowledge will converge to the mean-variance UE condition. Second, the convergence of route choice dynamics to a UE condition is not affected by adding a bounded weight on the daily perceived knowledge. Thirdly, non-UE-based formulations of perceived knowledge also lead to fixed points for the mean route choice proportion. The convergences of the models with different types of perceived knowledge are verified based on numerical studies and the underlying day-to-day route choice dynamics with both recurrent and non-recurrent unreliability are examined.

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  • Zhu, Zheng & Mardan, Atabak & Zhu, Shanjiang & Yang, Hai, 2021. "Capturing the interaction between travel time reliability and route choice behavior based on the generalized Bayesian traffic model," Transportation Research Part B: Methodological, Elsevier, vol. 143(C), pages 48-64.
    • Handle: RePEc:eee:transb:v:143:y:2021:i:c:p:48-64
    DOI: 10.1016/j.trb.2020.11.005
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    1. Cascetta, Ennio, 1989. "A stochastic process approach to the analysis of temporal dynamics in transportation networks," Transportation Research Part B: Methodological, Elsevier, vol. 23(1), pages 1-17, February.
    2. Chengjuan Zhu & Bin Jia & Linghui Han & Ziyou Gao, 2014. "Parking Pricing and Model Split under Uncertainty," Discrete Dynamics in Nature and Society, Hindawi, vol. 2014, pages 1-8, February.
    3. Watling, David, 2006. "User equilibrium traffic network assignment with stochastic travel times and late arrival penalty," European Journal of Operational Research, Elsevier, vol. 175(3), pages 1539-1556, December.
    4. Martin L. Hazelton & David P. Watling, 2004. "Computation of Equilibrium Distributions of Markov Traffic-Assignment Models," Transportation Science, INFORMS, vol. 38(3), pages 331-342, August.
    5. Lam, William H.K. & Shao, Hu & Sumalee, Agachai, 2008. "Modeling impacts of adverse weather conditions on a road network with uncertainties in demand and supply," Transportation Research Part B: Methodological, Elsevier, vol. 42(10), pages 890-910, December.
    6. Lam, Terence C. & Small, Kenneth A., 2003. "The Value of Time and Reliability: Measurement from a Value Pricing Experiment," University of California Transportation Center, Working Papers qt47s4z7z5, University of California Transportation Center.
    7. Fosgerau, Mogens & Karlström, Anders, 2010. "The value of reliability," Transportation Research Part B: Methodological, Elsevier, vol. 44(1), pages 38-49, January.
    8. Feng Xiao & Minyu Shen & Zhengtian Xu & Ruijie Li & Hai Yang & Yafeng Yin, 2019. "Day-to-Day Flow Dynamics for Stochastic User Equilibrium and a General Lyapunov Function," Transportation Science, INFORMS, vol. 53(3), pages 683-694, May.
    9. Arnott, Richard & de Palma, Andre & Lindsey, Robin, 1999. "Information and time-of-usage decisions in the bottleneck model with stochastic capacity and demand," European Economic Review, Elsevier, vol. 43(3), pages 525-548, March.
    10. Zhu, Zheng & Li, Xinwei & Liu, Wei & Yang, Hai, 2019. "Day-to-day evolution of departure time choice in stochastic capacity bottleneck models with bounded rationality and various information perceptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 131(C), pages 168-192.
    11. Parry, Katharina & Hazelton, Martin L., 2013. "Bayesian inference for day-to-day dynamic traffic models," Transportation Research Part B: Methodological, Elsevier, vol. 50(C), pages 104-115.
    12. Watling, David, 1999. "Stability of the stochastic equilibrium assignment problem: a dynamical systems approach," Transportation Research Part B: Methodological, Elsevier, vol. 33(4), pages 281-312, May.
    13. Hazelton, Martin L., 2002. "Day-to-day variation in Markovian traffic assignment models," Transportation Research Part B: Methodological, Elsevier, vol. 36(7), pages 637-648, August.
    14. Zhu, Zheng & Qin, Xiaoran & Ke, Jintao & Zheng, Zhengfei & Yang, Hai, 2020. "Analysis of multi-modal commute behavior with feeding and competing ridesplitting services," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 713-727.
    15. Small, Kenneth A, 1982. "The Scheduling of Consumer Activities: Work Trips," American Economic Review, American Economic Association, vol. 72(3), pages 467-479, June.
    16. Zhu, Shanjiang & Levinson, David & Liu, Henry X. & Harder, Kathleen, 2010. "The traffic and behavioral effects of the I-35W Mississippi River bridge collapse," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(10), pages 771-784, December.
    17. Fernando Ordóñez & Nicolás E. Stier-Moses, 2010. "Wardrop Equilibria with Risk-Averse Users," Transportation Science, INFORMS, vol. 44(1), pages 63-86, February.
    18. Michael J. Smith, 1984. "The Stability of a Dynamic Model of Traffic Assignment---An Application of a Method of Lyapunov," Transportation Science, INFORMS, vol. 18(3), pages 245-252, August.
    19. Lam, Terence C. & Small, Kenneth A., 0. "The value of time and reliability: measurement from a value pricing experiment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 37(2-3), pages 231-251, April.
    20. He, Xiaozheng & Guo, Xiaolei & Liu, Henry X., 2010. "A link-based day-to-day traffic assignment model," Transportation Research Part B: Methodological, Elsevier, vol. 44(4), pages 597-608, May.
    21. Guo, Ren-Yong & Yang, Hai & Huang, Hai-Jun & Tan, Zhijia, 2015. "Link-based day-to-day network traffic dynamics and equilibria," Transportation Research Part B: Methodological, Elsevier, vol. 71(C), pages 248-260.
    22. Hongbo Ye & Hai Yang, 2017. "Rational Behavior Adjustment Process with Boundedly Rational User Equilibrium," Transportation Science, INFORMS, vol. 51(3), pages 968-980, August.
    23. Shoichiro Nakayama, 2009. "Bayesian Learning, Day-to-day Adjustment Process, and Stability of Wardrop Equilibrium," Springer Books, in: William H. K. Lam & S. C. Wong & Hong K. Lo (ed.), Transportation and Traffic Theory 2009: Golden Jubilee, chapter 0, pages 425-440, Springer.
    24. Watling, David P. & Hazelton, Martin L., 2018. "Asymptotic approximations of transient behaviour for day-to-day traffic models," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 90-105.
    25. de Palma, André & Picard, Nathalie, 2005. "Route choice decision under travel time uncertainty," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(4), pages 295-324, May.
    26. Yang, Fan & Zhang, Ding, 2009. "Day-to-day stationary link flow pattern," Transportation Research Part B: Methodological, Elsevier, vol. 43(1), pages 119-126, January.
    27. Gary A. Davis & Nancy L. Nihan, 1993. "Large Population Approximations of a General Stochastic Traffic Assignment Model," Operations Research, INFORMS, vol. 41(1), pages 169-178, February.
    28. Lo, Hong K. & Tung, Yeou-Koung, 2003. "Network with degradable links: capacity analysis and design," Transportation Research Part B: Methodological, Elsevier, vol. 37(4), pages 345-363, May.
    29. Chen, Anthony & Zhou, Zhong & Lam, William H.K., 2011. "Modeling stochastic perception error in the mean-excess traffic equilibrium model," Transportation Research Part B: Methodological, Elsevier, vol. 45(10), pages 1619-1640.
    30. Ye, Hongbo & Yang, Hai, 2013. "Continuous price and flow dynamics of tradable mobility credits," Transportation Research Part B: Methodological, Elsevier, vol. 57(C), pages 436-450.
    31. Carlos F. Daganzo & Yosef Sheffi, 1977. "On Stochastic Models of Traffic Assignment," Transportation Science, INFORMS, vol. 11(3), pages 253-274, August.
    32. Yang, Hai, 1997. "Sensitivity analysis for the elastic-demand network equilibrium problem with applications," Transportation Research Part B: Methodological, Elsevier, vol. 31(1), pages 55-70, February.
    33. W. Burke Jackson & James V. Jucker, 1982. "An Empirical Study of Travel Time Variability and Travel Choice Behavior," Transportation Science, INFORMS, vol. 16(4), pages 460-475, November.
    34. Nie, Yu (Marco) & Wu, Xing, 2009. "Shortest path problem considering on-time arrival probability," Transportation Research Part B: Methodological, Elsevier, vol. 43(6), pages 597-613, July.
    35. Horowitz, Joel L., 1984. "The stability of stochastic equilibrium in a two-link transportation network," Transportation Research Part B: Methodological, Elsevier, vol. 18(1), pages 13-28, February.
    36. Small, Kenneth A., 2001. "The Value of Pricing," University of California Transportation Center, Working Papers qt0rm449sx, University of California Transportation Center.
    37. Nie, Yu (Marco), 2011. "Multi-class percentile user equilibrium with flow-dependent stochasticity," Transportation Research Part B: Methodological, Elsevier, vol. 45(10), pages 1641-1659.
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