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Pre-trip information and route-choice decisions with stochastic travel conditions: Theory

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  • Lindsey, Robin
  • Daniel, Terry
  • Gisches, Eyran
  • Rapoport, Amnon

Abstract

This paper studies the effects of pre-trip information on route-choice decisions when travel conditions are congested and stochastic. We adopt a model based on the classical two-route network in which free-flow travel times and/or capacities on each route vary unpredictably due to such shocks as bad weather, accidents, and special events. We show that the benefits of information depend on differences between routes in free-flow costs, the shape of the travel cost functions, the severity of congestion and capacity shocks, and the degree of correlation between routes in travel conditions. Information is more likely to be welfare-reducing when free-flow travel costs differ appreciably, travel cost functions are convex, shocks are similar in size on the routes, and route conditions are strongly and positively correlated.

Suggested Citation

  • Lindsey, Robin & Daniel, Terry & Gisches, Eyran & Rapoport, Amnon, 2014. "Pre-trip information and route-choice decisions with stochastic travel conditions: Theory," Transportation Research Part B: Methodological, Elsevier, vol. 67(C), pages 187-207.
    • Handle: RePEc:eee:transb:v:67:y:2014:i:c:p:187-207
    DOI: 10.1016/j.trb.2014.05.006
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    1. Zhaoqi Zang & Richard Batley & Xiangdong Xu & David Z. W. Wang, 2022. "On the value of distribution tail in the valuation of travel time variability," Papers 2207.06293, arXiv.org, revised Dec 2023.
    2. Yu, Xiaojuan & van den Berg, Vincent A.C. & Li, Zhi-Chun, 2023. "Congestion pricing and information provision under uncertainty: Responsive versus habitual pricing," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(C).
    3. Zhaoqi Zang & Xiangdong Xu & Kai Qu & Ruiya Chen & Anthony Chen, 2022. "Travel time reliability in transportation networks: A review of methodological developments," Papers 2206.12696, arXiv.org, revised Jul 2022.
    4. Kasun P Wijayaratna & Vinayak V Dixit & Laurent Denant-Boemont & S Travis Waller, 2017. "An experimental study of the Online Information Paradox: Does en-route information improve road network performance?," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-17, September.
    5. Han, Xiao & Yu, Yun & Gao, Zi-You & Zhang, H. Michael, 2021. "The value of pre-trip information on departure time and route choice in the morning commute under stochastic traffic conditions," Transportation Research Part B: Methodological, Elsevier, vol. 152(C), pages 205-226.
    6. Zhang, Zhao-Ze & Huang, Hai-Jun & Tang, Tie-Qiao, 2018. "Impacts of preceding information on travelers’ departure time behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 523-529.
    7. Fosgerau, Mogens & Jiang, Gege, 2019. "Travel time variability and rational inattention," Transportation Research Part B: Methodological, Elsevier, vol. 120(C), pages 1-14.
    8. Luan, Jianlin & Polak, John & Krishnan, Rajesh, 2019. "The structure of public-private sector collaboration in travel information markets: A game theoretic analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 129(C), pages 19-38.
    9. Levy, Nadav & Klein, Ido & Ben-Elia, Eran, 2018. "Emergence of cooperation and a fair system optimum in road networks: A game-theoretic and agent-based modelling approach," Research in Transportation Economics, Elsevier, vol. 68(C), pages 46-55.
    10. Qi, Hang & Jia, Ning & Qu, Xiaobo & He, Zhengbing, 2023. "Investigating day-to-day route choices based on multi-scenario laboratory experiments, Part I: Route-dependent attraction and its modeling," Transportation Research Part A: Policy and Practice, Elsevier, vol. 167(C).
    11. Ye, Hongbo & Xiao, Feng & Yang, Hai, 2021. "Day-to-day dynamics with advanced traveler information," Transportation Research Part B: Methodological, Elsevier, vol. 144(C), pages 23-44.
    12. Sun, Xiaoyan & Han, Xiao & Bao, Jian-Zhang & Jiang, Rui & Jia, Bin & Yan, Xiaoyong & Zhang, Boyu & Wang, Wen-Xu & Gao, Zi-You, 2017. "Decision dynamics of departure times: Experiments and modeling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 74-82.
    13. Wei, Fangfang & Jia, Ning & Ma, Shoufeng, 2016. "Day-to-day traffic dynamics considering social interaction: From individual route choice behavior to a network flow model," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 335-354.
    14. Jiang, Gege & Fosgerau, Mogens & Lo, Hong K., 2020. "Route choice, travel time variability, and rational inattention," Transportation Research Part B: Methodological, Elsevier, vol. 132(C), pages 188-207.
    15. Bifulco, Gennaro N. & Cantarella, Giulio E. & Simonelli, Fulvio & Velonà, Pietro, 2016. "Advanced traveller information systems under recurrent traffic conditions: Network equilibrium and stability," Transportation Research Part B: Methodological, Elsevier, vol. 92(PA), pages 73-87.
    16. Sun, Xiaoyan & Li, Wentao & Jiang, Rui & Zhu, Yubing & Chen, Dong, 2022. "Study on the influence of road capacity and information feedback on urban traffic system equilibrium state," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 593(C).

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