Heterogeneous traffic flow modeling with drivers' timid and aggressive characteristics
Cong Zhai(翟聪)1,2, Weitiao Wu(巫威眺)1,†, and Songwen Luo(罗淞文)1
1 School of Civil Engineering and Transportation, South China University of Technology, Guangzhou 510641, China; 2 School of Transportation and Civil Engineering and Architecture, Foshan University, Foshan 528000, China
Abstract The driver's characteristics (e.g., timid and aggressive) has been proven to greatly affect the traffic flow performance, whereas the underlying assumption in most of the existing studies is that all drivers are homogeneous. In the real traffic environment, the drivers are distinct due to a variety of factors such as personality characteristics. To better reflect the reality, we introduce the penetration rate to describe the degree of drivers' heterogeneity (i.e., timid and aggressive), and proceed to propose a generalized heterogeneous car-following model with different driver's characteristics. Through the linear stability analysis, the stability conditions of the proposed heterogeneous traffic flow model are obtained based on the perturbation method. The impacts of the penetration rate of drivers with low intensity, the average value and standard deviation of intensity parameters characterizing two types of drivers on the stability of traffic flow are analyzed by simulation. Results show that higher penetration of aggressive drivers contributes to traffic flow stability. The average value has a great impact on the stability of traffic flow, whereas the impact of the standard deviation is trivial.
(Granular models of complex systems; traffic flow)
Fund: Project supported by the Regional Joint Fund for Foundation and Applied Research Fund of Guangdong Province, China (Grant No. 2019A1515111200), Youth Innovation Talents Funds of Colleges and Universities in Guangdong Province, China (Grant No. 2018KQNCX287), the Science and Technology Program of Guangzhou, China (Grant No. 201904010202), the National Science Foundation of China (Grant No. 72071079), and the Science and Technology Program of Guangdong Province, China (Grant No. 2020A1414010010).
Cong Zhai(翟聪), Weitiao Wu(巫威眺), and Songwen Luo(罗淞文) Heterogeneous traffic flow modeling with drivers' timid and aggressive characteristics 2021 Chin. Phys. B 30 100507
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