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Managing bottleneck congestion with incentives

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  • Sun, Jian
  • Wu, Jiyan
  • Xiao, Feng
  • Tian, Ye
  • Xu, Xiangdong

Abstract

Incentive-Based Traffic Demand Management (IBTDM) is a strategy that adopts incentives to demotivate driving trips, or to redistribute demand across space and time. In this paper, we demonstrate the effectiveness of an IBTDM strategy that provides incentives to shift the commuting public's departure times so that the queueing delay is reduced. Based on Vickrey's bottleneck model, this paper considers the impact of incentive budget and market penetration rate on the optimal incentive profile for both homogeneous and heterogeneous commuters. The resulting departure pattern created by the optimal incentive profile achieves Pareto Optimality. The results indicate that an optimal incentive profile is “U-shape” during the morning peak with a limited budget. Additionally, we find that the marginal benefit of incentive is diminishing. Lastly, although Pareto improvement is achieved, commuters with higher values of time are found to benefit more under the optimal incentive design. It is also discovered that the incentive provider should promote IBTDM to the two ends of the income level of the commuters to achieve the lowest total system travel time under an insufficient marketing budget.

Suggested Citation

  • Sun, Jian & Wu, Jiyan & Xiao, Feng & Tian, Ye & Xu, Xiangdong, 2020. "Managing bottleneck congestion with incentives," Transportation Research Part B: Methodological, Elsevier, vol. 134(C), pages 143-166.
  • Handle: RePEc:eee:transb:v:134:y:2020:i:c:p:143-166
    DOI: 10.1016/j.trb.2020.01.010
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    Cited by:

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    2. Senlai Zhu & Hantao Yu & Congjun Fan, 2024. "Travel Plan Sharing and Regulation for Managing Traffic Bottleneck Based on Blockchain Technology," Sustainability, MDPI, vol. 16(4), pages 1-20, February.
    3. Li, Tianhao & Chen, Peng & Tian, Ye, 2021. "Personalized incentive-based peak avoidance and drivers’ travel time-savings," Transport Policy, Elsevier, vol. 100(C), pages 68-80.
    4. Bin Qiu & Yun Zhao, 2022. "Research on Improved Traffic Flow Prediction Network Based on CapsNet," Sustainability, MDPI, vol. 14(23), pages 1-17, November.
    5. Lucas Javaudin & Andrea Araldo & André de Palma, 2021. "Large-Scale Allocation of Personalized Incentives," THEMA Working Papers 2021-08, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    6. Li, Manzi & Jiang, Gege & Lo, Hong K., 2022. "Pricing strategy of ride-sourcing services under travel time variability," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 159(C).
    7. Fan, Wenbo & Xiao, Feng & Nie, Yu (Macro), 2022. "Managing bottleneck congestion with tradable credits under asymmetric transaction cost," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 158(C).
    8. Maurizio Faccio & Serena Finco & Ilenia Zennaro, 2021. "Sustainable People Home-Work Logistics: An Integrated Model of Circular Economy in the Chiampo Valley," Sustainability, MDPI, vol. 13(21), pages 1-13, October.
    9. Tian, Ye & Li, Yudi & Sun, Jian, 2022. "Stick or carrot for traffic demand management? Evidence from experimental economics," Transportation Research Part A: Policy and Practice, Elsevier, vol. 160(C), pages 235-254.
    10. Tian, Ye & Li, Yudi & Sun, Jian & Ye, Jianhong, 2021. "Characterizing favored users of incentive-based traffic demand management program," Transport Policy, Elsevier, vol. 105(C), pages 94-102.
    11. Wu, Jiyan & Tian, Ye & Sun, Jian, 2023. "Managing ridesharing with incentives in a bottleneck model," Research in Transportation Economics, Elsevier, vol. 101(C).
    12. Carlo Cenedese & Patrick Stokkink & Nikolas Gerolimins & John Lygeros, 2021. "Incentive-Based Electric Vehicle Charging for Managing Bottleneck Congestion," Papers 2111.05600, arXiv.org.
    13. Galit Cohen-Blankshtain & Hillel Bar-Gera & Yoram Shiftan, 2023. "Congestion pricing and positive incentives: conceptual analysis and empirical findings from Israel," Transportation, Springer, vol. 50(2), pages 607-633, April.

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