Commuting departure time choice under stochastic demand: Departure preferences and the value of information

Xiao Han, Yong Yang, Rui Jiang, Zi-You Gao and H. Michael Zhang

Transportation Research Part A: Policy and Practice, 2025, vol. 197, issue C

Abstract: This paper experimentally investigates morning commute behavior under stochastic demand and information provision. To understand the effects of information on departure time choice behavior and how commuters respond to the provided information under stochastic demand, we conducted a laboratory experiment involving two treatments with different amounts of information provided to the subjects. Our experimental results indicated that (I) the departure rates under different demands could be unified as a set of normalized departure rates, (II) feedback information affected departure time choice behavior, and more feedback information might induce worse outcomes (i.e., information paradox), (III) subjects showed heterogeneous departure time preferences, and providing more feedback information might make more subjects choose to depart early, and (IV) a small increase in the number of subjects with early departure preferences could increase traffic congestion under high demand and reduce the efficient use of transport systems. Our experimental studies shed light on the importance and complexity of information provision and departure time preferences on the morning commute traffic patterns and congestion.

Keywords: Departure time choice; Stochastic demand; Information provision; Departure preference; Laboratory experiment (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1016/j.tra.2025.104476

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