|Table of Contents|

[1] Li Manman, , Lu Jian, et al. Network traffic flow evolution with battery electric vehiclesand conventional gasoline vehicles [J]. Journal of Southeast University (English Edition), 2019, 35 (2): 213-219. [doi:10.3969/j.issn.1003-7985.2019.02.011]

Network traffic flow evolution with battery electric vehiclesand conventional gasoline vehicles()

Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

2019 2
Research Field:
Traffic and Transportation Engineering
Publishing date:


Network traffic flow evolution with battery electric vehiclesand conventional gasoline vehicles
Li Manman1 2 3 Lu Jian1 2 3 Sun Jiahui4 Tu Qiang3
1Jiangsu Key Laboratory of Urban ITS, Southeast University, Nanjing 210096, China
2Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Nanjing 210096, China
3School of Transportation, Southeast University, Nanjing 210096, China
4Xi’an Aerospace Power Test Technology Institute, Xi’an 710100, China
battery electric vehicles constrained path reinforcement learning bounded rationality traffic dynamics
In order to investigate the effect of the use of battery electric vehicles on traffic dynamics, the valid paths of electric battery vehicles are defined and a check-based method is proposed to obtain them. Then, assuming that travelers only focus on their past travel experience, a day-to-day traffic assignment model is established based on reinforcement learning and bounded rationality. In the proposed model, the Bush-Mosteller model, a reinforcement learning model, is modified to calculate path choice probability according to bounded rationality. The modified model updates the path choice probability only if the gap between expected travel time and perceived travel time is beyond the cognitive threshold. Numerical experiments validate the effectiveness of the model and show that traffic flows can converge to the equilibrium in any case of cognitive thresholds and penetration rates of battery electric vehicles. The cognitive threshold has a positive influence on the variation of traffic flows while it has a negative influence on the differences between traffic flows. The adaptation of battery electric vehicles leads to the poor performance of the traffic system.


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Biographies: Li Manman(1991—), female, Ph.D. candidate; Lu Jian(corresponding author), male, doctor, professor, lujian_1972@seu.edu.cn.
Foundation items: The National Natural Science Foundation of China(No.51478110), Postgraduate Research & Practice Innovation Program of Jiangsu Province(No.KYCX18_0139).
Citation: Li Manman, Lu Jian, Sun Jiahui, et al. Network traffic flow evolution with battery electric vehicles and conventional gasoline vehicles[J].Journal of Southeast University(English Edition), 2019, 35(2):213-219.DOI:10.3969/j.issn.1003-7985.2019.02.011.
Last Update: 2019-06-20