Hypercongestion, Autonomous Vehicles, and Urban Spatial Structure

Author:

Dantsuji Takao12ORCID,Takayama Yuki3ORCID

Affiliation:

1. Monash Institute of Transport Studies, Monash University, Clayton, Victoria 3800, Australia;

2. Institute of Science and Engineering, Kanazawa University, Kanazawa 920-1192, Japan;

3. Department of Civil and Environmental Engineering, Tokyo Institute of Technology, Tokyo 152-8550, Japan

Abstract

This paper examines the effects of hypercongestion mitigation by perimeter control and the introduction of autonomous vehicles on the spatial structures of cities. By incorporating a bathtub model, we develop a land use model where hypercongestion occurs in the downtown area and interacts with land use. We show that hypercongestion mitigation by perimeter control decreases the commuting cost in the short run and results in a less dense urban spatial structure in the long run. Furthermore, we reveal that the impact of autonomous vehicles depends on the presence of hypercongestion. The introduction of autonomous vehicles may increase the commuting cost in the presence of hypercongestion and may cause a decrease in the suburban population; however, it may make cities spatially expand outward. This result contradicts that of the standard bottleneck model. When perimeter control is implemented, the introduction of autonomous vehicles decreases the commuting cost and results in a less dense urban spatial structure. These results show that hypercongestion is a key factor that can change urban spatial structures. History: This paper has been accepted for the Transportation Science Special Issue on ISTTT25 Conference. Funding: This work was supported by ACT-X [Grant JPMJAX21AE], Fusion Oriented REsearch for disruptive Science and Technology [Grant JPMJFR215M], the Japan Society for the Promotion of Science [Grants 23K13422 and 22H01610], and the Council for Science, Technology and Innovation [Grant JPJ012187]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/trsc.2024.0519 .

Publisher

Institute for Operations Research and the Management Sciences (INFORMS)

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