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author:

Tang, Z.-Y. (Tang, Z.-Y..) [1] | Tian, L.-J. (Tian, L.-J..) [2] | Liu, P. (Liu, P..) [3] | Huang, H.-J. (Huang, H.-J..) [4]

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Abstract:

This study examines the effects of parking reservation schemes on travel choices and flow distribution in a commuting system comprising regular vehicles (RVs) and shared autonomous vehicles (SAVs), when faced with limited parking spaces. All possible departure patterns under three parking reservation schemes are explored, involving unreserved and reserved RV commuters, as well as SAV commuters. Associated factors, such as the number of parking slots, the number of unreserved slots, and the additional SAV cost, are analyzed. The impacts of these factors on various metrics, including modal split, SAV market share, traffic congestion, individual travel cost, and system performance, are investigated. Analytical analysis reveals that managing the numbers of parking slots and unreserved parking slots can reduce individual travel cost and alleviate traffic congestion. Additionally, the study suggests an optimal reservation scheme for the number of parking slots and the ratio of unreserved slots, along with the additional SAV cost, to minimize total travel cost and maximize system efficiency. These findings could shape future urban mobility parking policies, accommodating mixed traffic of regular and autonomous vehicles. © 2024 Elsevier Ltd

Keyword:

Bottleneck model Departure patterns Dynamic user equilibrium Parking reservation Shared autonomous vehicle

Community:

  • [ 1 ] [Tang Z.-Y.]School of Business, Guangxi University, Nanning, 530004, China
  • [ 2 ] [Tang Z.-Y.]School of Economics and Management, Fuzhou University, Fuzhou, 350108, China
  • [ 3 ] [Tian L.-J.]School of Business, Guangxi University, Nanning, 530004, China
  • [ 4 ] [Tian L.-J.]School of Economics and Management, Fuzhou University, Fuzhou, 350108, China
  • [ 5 ] [Liu P.]MOE Key Laboratory of Complex System Analysis and Management Decision, School of Economics and Management, Beihang University, Beijing, 100191, China
  • [ 6 ] [Huang H.-J.]MOE Key Laboratory of Complex System Analysis and Management Decision, School of Economics and Management, Beihang University, Beijing, 100191, China

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Source :

Transportation Research Part B: Methodological

ISSN: 0191-2615

Year: 2025

Volume: 192

5 . 8 0 0

JCR@2023

CAS Journal Grade:1

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ESI Highly Cited Papers on the List: 0 Unfold All

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Chinese Cited Count:

30 Days PV: 0

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