Autonomous cars and activity-based bottleneck model:How do in-vehicle activities determine aggregate travel patterns?

Xiaojuan Yu*, Vincent A.C. van den Berg, Erik T. Verhoef

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

When traveling in an autonomous car, the travel time can be used for performing activities other than driving. This paper distinguishes users’ work-related and home-related activities in autonomous cars and proposes an activity-based bottleneck model to investigate travelers’ behavior in the morning commute, shedding light on how the scope to undertake in-vehicle activities affects travelers’ trip-timing preferences and decisions, and therewith social welfare. These welfare effects can be expected to depend on the optimality of both the market for trips, and the market for vehicles. We therefore consider different supply regimes for vehicles, as well as unpriced congestion versus queue-eliminating road pricing. We reveal analytically the relationship between various in-vehicle activities and trip-timing decisions by users of autonomous and normal cars. Three supply regimes for autonomous cars are investigated: welfare-maximizing public supply, competitive marginal cost supply, and profit-maximizing private supply. Pricing rules under different supply regimes are compared analytically, and the relative efficiencies in terms of the welfare gains are compared numerically. The results show that travelers’ in-vehicle activity choices have significant impacts on travel patterns, congestion externality, supply decisions, and the associated welfare effects.

Original languageEnglish
Article number103641
Pages (from-to)1-29
Number of pages29
JournalTransportation Research Part C: Emerging Technologies
Volume139
Early online date13 Apr 2022
DOIs
Publication statusPublished - Jun 2022

Bibliographical note

Funding Information:
We thank three anonymous referees for their helpful comments and constructive suggestions on an earlier draft of the paper. We also thank Professor Zhi-Chun Li of Huazhong University of Science and Technology for helpful comments. The work described in this paper was jointly supported by grants from the National Key Research and Development Program of China ( 2018YFB1600900 ), the National Natural Science Foundation of China ( 71525003 , 71890970/71890974 ), and the NSFC-EU joint research project (71961137001). Any remaining errors are ours.

Publisher Copyright:
© 2022 The Authors

Keywords

  • Activity-based modeling
  • Autonomous cars
  • Bottleneck model
  • Private vs public supply
  • Traffic congestion

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