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A unified equilibrium framework of new shared mobility systems

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  • Di, Xuan
  • Ban, Xuegang Jeff

Abstract

Modeling congestion effects arising from multiple travel modes, shared mobility modes in particular, is non-trivial because of the complex interactions among diverse agents and distinct traffic flow compositions. This research aims to provide a theoretical framework of generic traffic network equilibria to unify these services and hopefully become a step stone to modeling shared mobility services in congested road network. In the proposed framework, we mainly focus on three modes: driving solo, ridesharing, and e-hailing service. The four types of traffic flows are: personal vehicle drivers, e-hailing drivers, ridesharing riders, and e-hailing passengers. The first two flows contribute to traffic congestion while the latter two do not. To capture their interactions, a super extended network is created with four copied networks each of whom represents one type of traffic flow. The equilibrium of new mobility systems can then be reformulated as a quasi-variational inequality and solution existence is discussed. The numerical results are tested in both Braess network and Sioux Falls network to illustrate the impact of different parameters on equilibrium outcomes, including modal cost, system travel time and deadhead miles. The results of this model will help assist transportation planners in making policy and regulation decisions regarding shared mobility services.

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  • Di, Xuan & Ban, Xuegang Jeff, 2019. "A unified equilibrium framework of new shared mobility systems," Transportation Research Part B: Methodological, Elsevier, vol. 129(C), pages 50-78.
    • Handle: RePEc:eee:transb:v:129:y:2019:i:c:p:50-78
    DOI: 10.1016/j.trb.2019.09.002
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    3. Xingyuan Li & Jing Bai, 2021. "A Ridesharing Choice Behavioral Equilibrium Model with Users of Heterogeneous Values of Time," IJERPH, MDPI, vol. 18(3), pages 1-22, January.
    4. van den Berg, Vincent A.C. & Meurs, Henk & Verhoef, Erik T., 2022. "Business models for Mobility as an Service (MaaS)," Transportation Research Part B: Methodological, Elsevier, vol. 157(C), pages 203-229.
    5. Rui Yao & Shlomo Bekhor, 2023. "A general equilibrium model for multi-passenger ridesharing systems with stable matching," Papers 2303.16595, arXiv.org, revised Dec 2023.
    6. Noruzoliaee, Mohamadhossein & Zou, Bo, 2022. "One-to-many matching and section-based formulation of autonomous ridesharing equilibrium," Transportation Research Part B: Methodological, Elsevier, vol. 155(C), pages 72-100.
    7. Sun, S. & Szeto, W.Y., 2021. "Multi-class stochastic user equilibrium assignment model with ridesharing: Formulation and policy implications," Transportation Research Part A: Policy and Practice, Elsevier, vol. 145(C), pages 203-227.
    8. Hu, Shichun & Dessouky, Maged M. & Uhan, Nelson A. & Vayanos, Phebe, 2021. "Cost-sharing mechanism design for ride-sharing," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 410-434.
    9. Ding, Xiaoshu & Qi, Qi & Jian, Sisi & Yang, Hai, 2023. "Mechanism design for Mobility-as-a-Service platform considering travelers’ strategic behavior and multidimensional requirements," Transportation Research Part B: Methodological, Elsevier, vol. 173(C), pages 1-30.
    10. Noruzoliaee, Mohamadhossein & Zou, Bo & Zhou, Yan (Joann), 2021. "Truck platooning in the U.S. national road network: A system-level modeling approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).
    11. Zhong, Lin & Zhang, Kenan & (Marco) Nie, Yu & Xu, Jiuping, 2020. "Dynamic carpool in morning commute: Role of high-occupancy-vehicle (HOV) and high-occupancy-toll (HOT) lanes," Transportation Research Part B: Methodological, Elsevier, vol. 135(C), pages 98-119.
    12. Yao, Rui & Bekhor, Shlomo, 2023. "A general equilibrium model for multi-passenger ridesharing systems with stable matching," Transportation Research Part B: Methodological, Elsevier, vol. 175(C).

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