Study on the influence of road capacity and information feedback on urban traffic system equilibrium state

Xiaoyan Sun, Wentao Li, Rui Jiang, Yubing Zhu and Dong Chen

Physica A: Statistical Mechanics and its Applications, 2022, vol. 593, issue C

Abstract: This paper presents an experimental study on the equilibrium state transition of a traffic system under road capacity changes. The experiments were based on a discrete bottleneck model. Four groups of experiments are conducted under two types of information feedback conditions. The experimental results show that it needs a long time for traffic system to approach a stable state when road capacity is reduced. However, players can adjust their decision-making rapidly and system can approach a stable state in a short time when road capacity is increased. The individuals’ choice behavior is analyzed in detail, and the analysis results show that an individual’s payoff will decrease if he/she frequently changes travel decisions. The Mann–Whitney U tests show information feedback has no significant influence on both the collective behavior of system and the players’ choice behavior. A reinforcement learning model is used to verify the experimental results, and the simulation results are in good agreement with the experimental results. The research can provide some theoretical references for urban traffic management.

Keywords: Urban traffic; Road capacity; Departure time choice behavior; User equilibrium (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:593:y:2022:i:c:s0378437122000504

DOI: 10.1016/j.physa.2022.126935

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