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The valuation of travel time reliability: does congestion matter?

Author

Listed:
  • Yu Xiao

    (Department of Civil and Environmental Engineering [Tokyo] - TITECH - Tokyo Institute of Technology [Tokyo])

  • Nicolas Coulombel

    (LVMT - Laboratoire Ville, Mobilité, Transport - IFSTTAR - Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux - UPEM - Université Paris-Est Marne-la-Vallée - ENPC - École des Ponts ParisTech)

  • André de Palma

    (KU Leuven - Catholic University of Leuven = Katholieke Universiteit Leuven, ENS Cachan - École normale supérieure - Cachan)

Abstract

This paper addresses the valuation of travel time reliability in the presence of endogenous congestion and the role of scheduling preferences. The bottleneck model of road congestion is amended by considering stochastic travel times. We thereby take into account the influence of travel time variability on the congestion profile. The cost of travel time variability is the same with exogenous or endogenous congestion for two classes of preferences: linear marginal utility of time (MUT) at work and constant-exponential MUT. Therefore, cost-benefit analyses of travel time reliability improvements yield consistent results even if departure time adjustments are not accounted for. For α − β − γ preferences, departure time adjustments decrease congestion, which strongly mitigates the cost of travel time variability. Cost-benefit analyses need in this case to explicitly consider the departure time choice, to avoid being biased for the rush hour period (when congestion is strong). A method is proposed to correct this bias when necessary.

Suggested Citation

  • Yu Xiao & Nicolas Coulombel & André de Palma, 2017. "The valuation of travel time reliability: does congestion matter?," Post-Print hal-01465956, HAL.
    • Handle: RePEc:hal:journl:hal-01465956
    DOI: 10.1016/j.trb.2016.12.003
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    3. Li, Zheng & Hensher, David A. & Rose, John M., 2010. "Willingness to pay for travel time reliability in passenger transport: A review and some new empirical evidence," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(3), pages 384-403, May.
    4. Khademi, Navid & Kharrazi, Hamed & Chen, Anthony & Chaiyasarn, Krisada & Zerguini, Seghir, 2024. "Departure time choices and a modeling framework for a guidance system," Journal of choice modelling, Elsevier, vol. 51(C).
    5. 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).
    6. 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.
    7. Sun, Xuting & Chung, Sai-Ho & Choi, Tsan-Ming & Sheu, Jiuh-Biing & Ma, Hoi Lam, 2020. "Combating lead-time uncertainty in global supply chain's shipment-assignment: Is it wise to be risk-averse?," Transportation Research Part B: Methodological, Elsevier, vol. 138(C), pages 406-434.
    8. Pudāne, Baiba, 2019. "Departure Time Choice and Bottleneck Congestion with Automated Vehicles: Role of On-board Activities," MPRA Paper 96328, University Library of Munich, Germany.
    9. Li, Zhi-Chun & Huang, Hai-Jun & Yang, Hai, 2020. "Fifty years of the bottleneck model: A bibliometric review and future research directions," Transportation Research Part B: Methodological, Elsevier, vol. 139(C), pages 311-342.
    10. Long, Jiancheng & Tan, Weimin & Szeto, W.Y. & Li, Yao, 2018. "Ride-sharing with travel time uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 143-171.

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