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Departure Times in Y-Shaped Traffic Networks with Multiple Bottlenecks

Author

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  • Terry E. Daniel
  • Eyran J. Gisches
  • Amnon Rapoport

Abstract

We study the departure time decisions of commuters traversing a traffic network with the goal of arriving at a common destination at a specified time. There are costs associated with arriving either too early or too late, and with delays experienced at bottlenecks. Our main hypothesis, based on the Nash equilibrium distribution of departure times, implies that, for certain parameter values, expanding the capacity of an upstream bottleneck can increase the total travel costs in the network. We report the results of a large-group laboratory experiment, which are strongly supportive of this counterintuitive hypothesis, and we discuss the implications. (JEL D85, R41)

Suggested Citation

  • Terry E. Daniel & Eyran J. Gisches & Amnon Rapoport, 2009. "Departure Times in Y-Shaped Traffic Networks with Multiple Bottlenecks," American Economic Review, American Economic Association, vol. 99(5), pages 2149-2176, December.
    • Handle: RePEc:aea:aecrev:v:99:y:2009:i:5:p:2149-76
    Note: DOI: 10.1257/aer.99.5.2149
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    References listed on IDEAS

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    Cited by:

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    2. Berliant, Marcus, 2011. "Repeated Commuting," MPRA Paper 28979, University Library of Munich, Germany.
    3. Rapoport, Amnon & Stein, William E. & Mak, Vincent & Zwick, Rami & Seale, Darryl A., 2010. "Endogenous arrivals in batch queues with constant or variable capacity," Transportation Research Part B: Methodological, Elsevier, vol. 44(10), pages 1166-1185, December.
    4. Ren-Yong Guo & Hai Yang & Hai-Jun Huang, 2018. "Are We Really Solving the Dynamic Traffic Equilibrium Problem with a Departure Time Choice?," Transportation Science, INFORMS, vol. 52(3), pages 603-620, June.
    5. Bao, Yue & Verhoef, Erik T. & Koster, Paul, 2021. "Leaving the tub: The nature and dynamics of hypercongestion in a bathtub model with a restricted downstream exit," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    6. Fu, Haoran & Akamatsu, Takashi & Satsukawa, Koki & Wada, Kentaro, 2022. "Dynamic traffic assignment in a corridor network: Optimum versus equilibrium," Transportation Research Part B: Methodological, Elsevier, vol. 161(C), pages 218-246.
    7. Vinayak V Dixit & Laurent Denant-Boemont, 2014. "Is Equilibrium in Transport Pure Nash, Mixed or Stochastic? Evidence from Laboratory Experiments," Post-Print halshs-01103472, HAL.
    8. Conte, Anna & Scarsini, Marco & Sürücü, Oktay, 2015. "Does time pressure impair performance? An experiment on queueing behavior," Center for Mathematical Economics Working Papers 538, Center for Mathematical Economics, Bielefeld University.
    9. 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.
    10. Wang, Tao & Liao, Peng & Tang, Tie-Qiao & Huang, Hai-Jun, 2022. "Deterministic capacity drop and morning commute in traffic corridor with tandem bottlenecks: A new manifestation of capacity expansion paradox," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 168(C).
    11. Miller, Harvey J., 2013. "Beyond sharing: cultivating cooperative transportation systems through geographic information science," Journal of Transport Geography, Elsevier, vol. 31(C), pages 296-308.
    12. Xiao Han & Yun Yu & Bin Jia & Zi‐You Gao & Rui Jiang & H. Michael Zhang, 2021. "Coordination Behavior in Mode Choice: Laboratory Study of Equilibrium Transformation and Selection," Production and Operations Management, Production and Operations Management Society, vol. 30(10), pages 3635-3656, October.
    13. Sakai, Takara & Akamatsu, Takashi & Satsukawa, Koki, 2024. "Queue replacement principle for corridor problems with heterogeneous commuters," Transportation Research Part B: Methodological, Elsevier, vol. 187(C).
    14. 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.
    15. Guo, Ren-Yong & Yang, Hai & Huang, Hai-Jun & Li, Xinwei, 2018. "Day-to-day departure time choice under bounded rationality in the bottleneck model," Transportation Research Part B: Methodological, Elsevier, vol. 117(PB), pages 832-849.
    16. Rapoport, Amnon & Qi, Hang & Mak, Vincent & Gisches, Eyran J., 2019. "When a few undermine the whole: A class of social dilemmas in ridesharing," Journal of Economic Behavior & Organization, Elsevier, vol. 166(C), pages 125-137.
    17. Rapoport, Amnon & Gisches, Eyran J. & Daniel, Terry & Lindsey, Robin, 2014. "Pre-trip information and route-choice decisions with stochastic travel conditions: Experiment," Transportation Research Part B: Methodological, Elsevier, vol. 68(C), pages 154-172.

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    More about this item

    JEL classification:

    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise

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    1. Departure Times in Y-Shaped Traffic Networks with Multiple Bottlenecks (AER 2009) in ReplicationWiki

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