Social optimum for evening commute in a single-entry traffic corridor with no early departures

Li, Chuan-Yao; Xu, Guangming; Tang, Tie-Qiao

doi:10.1016/j.physa.2018.02.098

Cited by 6 publications

(1 citation statement)

References 33 publications

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“…Di et al [31] stimulated the impacts of bounded rationality on the drivers' route choice behavior. en, Li et al [32,33] explored the relationship between bounded rationality and commuting behaviors. Jiang and Deng [34] proposed a Bayesian network to describe travel time distribution based on bounded rationality.…”

Section: Bounded Rationality Applied In the Car-following Modelmentioning

confidence: 99%

Trip Cost Estimation of Connected Autonomous Vehicle Mixed Traffic Flow in a Two-Route Traffic Network

Liu

Chen

et al. 2020

Journal of Advanced Transportation

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With the advancement of connected autonomous vehicle (CAV) technology, research on future traffic conditions after the popularization of CAVs needs to be resolved urgently. Bounded rationality of human drivers is essential for simulating traffic flow precisely, but few studies focus on the traffic flow simulation considered bounded rationality in CAV mixed traffic flow. In this study, we introduce random bounded rationality into the hybrid feedback strategy (HFS) under CAV mixed traffic flow to explore the impacts of CAV penetration rate on the trip cost of vehicles. First, we investigated the bounded rationality of drivers, and we found that it follows normal contribution. Then, we proposed HFS considering random bounded rationality and the CAV penetration rate to simulate the traffic condition. The numerical results show that the enhancement of the CAV penetration rate could reduce total trip cost. The research could help us to simulate the CAVs mixed traffic flow more precisely and realistically.

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