Equilibrium analysis of morning commuting and parking under spatial capacity allocation in the autonomous vehicle environment

Xiang Zhang, Wei Liu, Michael Levin, S. Travis Waller

Research output: Journal article publicationJournal articleAcademic researchpeer-review

9 Citations (Scopus)

Abstract

This study analytically investigates the morning commuting and parking patterns of autonomous vehicles (AVs) under different spatial road capacity allocation schemes (i.e., capacity split between inbound and outbound travel directions). Given that self-driving AV might park far away from commuters’ destination, we investigate equilibrium departure/arrival and parking patterns for AVs subject to the spatial road capacity allocation. We also analyse the system optimum traffic pattern for AV morning commute under a given capacity allocation scheme. Furthermore, we examine optimal capacity allocation strategies under user equilibrium and system optimum AV traffic patterns, respectively, which aim to minimise the total system travel cost. Numerical studies are conducted to illustrate the model and analysis. The results reveal the sensitivity of different efficiency metrics with respect to AV parking supply and road capacity allocation schemes, and provide insights into the infrastructure management with future automated transport.

Original languageEnglish
Article number103071
JournalTransportation Research Part E: Logistics and Transportation Review
Volume172
DOIs
Publication statusPublished - Apr 2023

Keywords

  • Autonomous vehicles
  • Bottleneck model
  • Morning commute
  • Spatial capacity allocation
  • System optimum
  • User equilibrium

ASJC Scopus subject areas

  • Business and International Management
  • Civil and Structural Engineering
  • Transportation

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