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Modeling Impacts of Implementation Policies of Tradable Credit Schemes on Traffic Congestion in the Context of Traveler’s Cognitive Illusion

Author

Listed:
  • Fei Han

    (Engineering Research Center of Ministry of Education for Road Transportation Decarbonization, Chang’an University, Xi’an 710064, China
    College of Transportation Engineering, Chang’an University, Xi’an 710064, China)

  • Jian Wang

    (School of Transportation, Southeast University, Nanjing 211189, China)

  • Lingli Huang

    (School of Humanities and Arts, Xi’an International University, Xi’an 710077, China)

  • Yan Li

    (College of Transportation Engineering, Chang’an University, Xi’an 710064, China)

  • Liu He

    (Department of Automation, Nanjing University of Science and Technology, Nanjing 210094, China)

Abstract

A tradable credit scheme (TCS) is a novel traffic demand management (TDM) measure that can effectively mitigate traffic congestion in a revenue-neutral way. Under a given TCS, the cognitive illusion (CI) would occur when travelers instinctively use a specious thinking logic to estimate travel cost. The traveler’s CI would significantly influence his/her route choice behaviors, and thus the regulation effect of TCS on mitigating traffic congestion. To reveal the impacts of implementation policies of TCS on managing network mobility in the context of the traveler’s CI, this study investigated the traffic equilibrium assignment model with consideration of the traveler’s CI and the specific implementation policies of TCS. By incorporating the two types of factors into the generalized path travel cost (GPTC), the coupled user equilibrium (UE) and market equilibrium (ME) conditions are established to describe the equilibrium state of the traffic network under a given TCS. As the implementation policies of TCS are factored in the GPTC, different types of initial credit distribution scheme (ICDS) and the transaction costs (TC) of trading credits can be analyzed within the unified model framework. The coupled UE and ME conditions are then reformulated as an equivalent variational inequality (VI) model, and the sufficient conditions for the uniqueness of UE link flows and ME credit price are also provided. The system optimal (SO) TCS design problem is further investigated to achieve the minimum total travel time (TTT) of the transportation network, and two analytical methods are proposed to obtain the SO TCS in the context of the traveler’s CI. Numerical experiments are presented to verify the proposed model and methods. The results show that the presence of the traveler’s CI has an effect of lowering the ME credit price, and ICDS and TC have a complex network-wide influence on the ME credit price and UE link flows, which depends on the specific values of the relevant parameters.

Suggested Citation

  • Fei Han & Jian Wang & Lingli Huang & Yan Li & Liu He, 2023. "Modeling Impacts of Implementation Policies of Tradable Credit Schemes on Traffic Congestion in the Context of Traveler’s Cognitive Illusion," Sustainability, MDPI, vol. 15(15), pages 1-18, July.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:15:p:11643-:d:1204558
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    References listed on IDEAS

    as
    1. Louis Balzer & Ludovic Leclercq, 2021. "Modal equilibrium of a tradable credit scheme with a trip-based MFD and logit-based decision-making," Papers 2112.07277, arXiv.org, revised Apr 2022.
    2. Bao, Yue & Verhoef, Erik T. & Koster, Paul, 2019. "Regulating dynamic congestion externalities with tradable credit schemes: Does a unique equilibrium exist?," Transportation Research Part B: Methodological, Elsevier, vol. 127(C), pages 225-236.
    3. Angelelli, E. & Morandi, V. & Savelsbergh, M. & Speranza, M.G., 2021. "System optimal routing of traffic flows with user constraints using linear programming," European Journal of Operational Research, Elsevier, vol. 293(3), pages 863-879.
    4. Xiao, Feng & Long, Jiancheng & Li, Lu & Kou, Gang & Nie, Yu, 2019. "Promoting social equity with cyclic tradable credits," Transportation Research Part B: Methodological, Elsevier, vol. 121(C), pages 56-73.
    5. Xiao, Feng & Qian, Zhen (Sean) & Zhang, H. Michael, 2013. "Managing bottleneck congestion with tradable credits," Transportation Research Part B: Methodological, Elsevier, vol. 56(C), pages 1-14.
    6. Larsson, Torbjorn & Patriksson, Michael & Stromberg, Ann-Brith, 1996. "Conditional subgradient optimization -- Theory and applications," European Journal of Operational Research, Elsevier, vol. 88(2), pages 382-403, January.
    7. Fei Han & Lin Cheng, 2016. "The Role of Initial Credit Distribution Scheme in Managing Network Mobility and Maximizing Reserve Capacity: Considering Traveler’s Cognitive Illusion," Discrete Dynamics in Nature and Society, Hindawi, vol. 2016, pages 1-12, March.
    8. Erel Avineri, 2006. "The Effect of Reference Point on Stochastic Network Equilibrium," Transportation Science, INFORMS, vol. 40(4), pages 409-420, November.
    9. Zhang, Fang & Lu, Jian & Hu, Xiaojian & Fan, Ruochuan & Chen, Junlan, 2022. "Managing bottleneck congestion with tradable credit scheme under demand uncertainty," Research in Transportation Economics, Elsevier, vol. 95(C).
    10. 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).
    11. He, Fang & Yin, Yafeng & Shirmohammadi, Nima & Nie, Yu (Marco), 2013. "Tradable credit schemes on networks with mixed equilibrium behaviors," Transportation Research Part B: Methodological, Elsevier, vol. 57(C), pages 47-65.
    12. Yang, Hai & Wang, Xiaolei, 2011. "Managing network mobility with tradable credits," Transportation Research Part B: Methodological, Elsevier, vol. 45(3), pages 580-594, March.
    13. Wang, Xiaolei & Yang, Hai & Zhu, Daoli & Li, Changmin, 2012. "Tradable travel credits for congestion management with heterogeneous users," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(2), pages 426-437.
    14. Yu Nie, 2015. "A New Tradable Credit Scheme for the Morning Commute Problem," Networks and Spatial Economics, Springer, vol. 15(3), pages 719-741, September.
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