4.5 Article

A simulation-based approach to investigate the driver route choice behavior under the connected vehicle environment

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.trf.2018.04.008

关键词

Fuel consumption; Connected vehicles; Driving behavior; Simulation; Agent

资金

  1. National Natural Science Foundation of China [U1564212, U1664262, U1764265, 61773040]
  2. Young Elite Scientist Sponsorship Program by the China Association for Science and Technology [2017QNRC001]

向作者/读者索取更多资源

Drivers can move with the real-time traffic information under the connected vehicle environment. Meanwhile, individual driving behavior (e.g., route choice) can influence the traffic state of the connected vehicle. This study contributes to investigate the relationship between the performance of traffic system and the driver route choice behavior in the connected vehicle environment. Especially, the heterogeneity of drivers in attention to fuel consumption and travel time is considered. A dynamic process of commuter day-to-day route choice behavior under the connected vehicle environment was proposed, the driving experience and the real-time information that affect the driver route choice are taken into considered simultaneously. Using the multi-agent simulation approach, the microcosmic and macroscopic behaviors of driver-vehicle-unit agents were described. A series of simulation experiments were conducted under the different percentages of drivers who pay enough attention to fuel consumption, and then simulation results were compared. The simulation results demonstrated that the performance of traffic state is better when enough drivers put emphasis on fuel consumption, and the optimal percentage of these drivers is about 60%. It is indicated that the travel time is more sensitive to the change of traffic state than fuel consumption, and the traffic system with enough drivers who care the fuel consumption could bring the better performance. This study has a guidance function to the application and promotion of eco-driving for government to optimize the structure of different types of drivers in the connected vehicle environment. (C) 2018 Elsevier Ltd. All rights reserved.

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