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The morning commute problem with endogenous shared autonomous vehicle penetration and parking space constraint

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  • Tian, Li-Jun
  • Sheu, Jiuh-Biing
  • Huang, Hai-Jun

Abstract

Morning commuting trips commonly involve a number of transportation modes and departure times. This study extends the standard bottleneck model by considering both regular and shared autonomous vehicles with and without parking space constraint, taking into account the travel time-dependent fuel cost that is associated with each vehicle. In this study the parking space constraint has no effect on shared autonomous vehicles and only commuters who share autonomous vehicles exhibit ridesharing behavior, differing from those utilizing regular vehicles. The dynamic departure patterns and endogenous penetration rates associated with shared autonomous vehicles are determined with respect to parking capacity. Analytical results not only provide several important propositions, but also include the optimal solutions for parking capacity and ridesharing occupancy from the perspective of the system optimum in terms of various indicators, under which parking capacity is a binding constraint, and the first shared autonomous vehicle arrives at the bottleneck as the last regular vehicle leaves. This work is expected not only to motivate related research, but also to promote the development of new strategies and methods for allocating a limited number of parking spaces and regulating the travel behavior of commuters in urban areas.

Suggested Citation

  • Tian, Li-Jun & Sheu, Jiuh-Biing & Huang, Hai-Jun, 2019. "The morning commute problem with endogenous shared autonomous vehicle penetration and parking space constraint," Transportation Research Part B: Methodological, Elsevier, vol. 123(C), pages 258-278.
    • Handle: RePEc:eee:transb:v:123:y:2019:i:c:p:258-278
    DOI: 10.1016/j.trb.2019.04.001
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    4. Zipeng Zhang & Ning Zhang, 2021. "Early Bird Scheme for Parking Management: How Does Parking Play a Role in the Morning Commute Problem," Sustainability, MDPI, vol. 13(15), pages 1-19, July.
    5. Xiao, Ling-Ling & Liu, Tian-Liang & Huang, Hai-Jun & Liu, Ronghui, 2021. "Temporal-spatial allocation of bottleneck capacity for managing morning commute with carpool," Transportation Research Part B: Methodological, Elsevier, vol. 143(C), pages 177-200.
    6. Lu, Xiao-Shan & Guo, Ren-Yong & Huang, Hai-Jun & Xu, Xiaoming & Chen, Jiajia, 2021. "Equilibrium analysis of parking for integrated daily commuting," Research in Transportation Economics, Elsevier, vol. 90(C).
    7. Zhang, Yuan & Zhao, Hui & Jiang, Rui, 2024. "Manage morning commute for household travels with parking space constraints," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 185(C).
    8. Yinying He & Csaba Csiszár, 2020. "Concept of Mobile Application for Mobility as a Service Based on Autonomous Vehicles," Sustainability, MDPI, vol. 12(17), pages 1-16, August.
    9. Zhen Wang & Haiyun Chen & Ting Zhu & Jiazhen Huo, 2024. "Is It Necessarily Better for More Commuters to Share a Vehicle?," Sustainability, MDPI, vol. 16(16), pages 1-23, August.
    10. Xiaojuan Yu & Vincent A.C. van den Berg, 2024. "Human-driven vehicles’ cruising versus autonomous vehicles’ back- and-forth congestion: The effects on traveling, parking and congestion," Tinbergen Institute Discussion Papers 24-032/VIII, Tinbergen Institute.
    11. Lu, Xiao-Shan & Huang, Hai-Jun & Guo, Ren-Yong & Xiong, Fen, 2021. "Linear location-dependent parking fees and integrated daily commuting patterns with late arrival and early departure in a linear city," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 293-322.
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