Simulating impacts of Automated Mobility-on-Demand on accessibility and residential relocation

Automated vehicles (AVs) have great potential to revolutionize the transportation sector and landscapes of future cities. The impacts of AVs on urban space, however, are far from clear. Mobility-on-Demand (MOD) services, on the other hand, are readily available in many places. This study seeks to explore (1) how Automated Mobility-on-Demand (AMOD) might affect urban residents' levels of accessibility and their residential relocation decisions; and (2) how these impacts might vary across space and socioeconomic groups. The authors use an agent-based microsimulation platform to assess two future AMOD scenarios in Singapore relative to a baseline. Results suggest that the addition of AMOD could enhance the overall accessibility of the population, but not if private transport modes, including private cars, taxis, and human-driven on-demand services, are prohibited. On the other hand, if private modes are eliminated, AMOD could alleviate inequality in accessibility as it appears to benefit the disadvantaged socioeconomic groups to a larger extent. The authors also find that AMOD deployment would not induce outward migration, nor would it increase home-work location imbalance. This study demonstrates how large-scale microsimulation can be leveraged to assess AMOD scenarios. The findings have some implications for preparing for the inevitable and potentially disruptive emergence of AVs.

• Record URL:
  https://doi.org/10.1016/j.cities.2021.103345
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S0264275121002456
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/02642751
• Supplemental Notes:
  • © 2021 Published by Elsevier Ltd. Abstract reprinted with permission of Elsevier.
• Authors:
  • Zhou, Meng
  • Le, Diem-Trinh
  • Nguyen-Phuoc, Duy Quy
  • Zegras, P Christopher
  • Ferreira Jr, Joseph
• Publication Date: 2021-11

Language

• English

Media Info

• Media Type: Web
• Features: Appendices; Figures; Maps; References; Tables;
• Pagination: 103345
• Serial:
  • Cities
  • Volume: 118
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 0264-2751
  • Serial URL: http://www.sciencedirect.com/science/journal/02642751

Subject/Index Terms

• TRT Terms: Accessibility; Autonomous vehicles; Demand responsive transportation; Equity; Microsimulation; Mobility
• Geographic Terms: Singapore
• Subject Areas: Data and Information Technology; Highways; Planning and Forecasting; Society; Vehicles and Equipment;

Filing Info

• Accession Number: 01783729
• Record Type: Publication
• Files: TRIS
• Created Date: Sep 29 2021 9:33AM