https://doi.org/10.1140/epjb/e2020-10028-3
Regular Article
Car-following model considering the lane-changing prevention effect and its stability analysis
1
School of Transportation and Logistics, Southwest Jiaotong University,
No.999 Piduquxianlu,
Chengdu
611756, P.R. China
2
Traffic Management Research Institute of the Ministry of Public Security,
Wuxi,
Jiangsu 214151, P.R. China
3
Institute of Artificial Intelligence, School of Information Science and Technology, Southwest Jiaotong University,
Chengdu
611756, P.R. China
4
National Engineering Laboratory of Integrated Transportation Big Data Application Technology, Southwest Jiaotong University,
Chengdu
611756, P.R. China
a e-mail: guoqianlt@swjtu.edu.cn
Received:
11
January
2020
Received in final form:
15
April
2020
Published online: 10 August 2020
The car-following behavior has attracted much attention in past decades. However, the majority of the existing studies ignored the fact that the following vehicle in car-following may prevent the lane-changing of the vehicle on the adjacent lanes, when a large gap exists between the following and leading vehicles. Therefore, this paper proposes a new car-following model considering the lane-changing prevention effect. The final velocity of the following vehicle is a combination of a safe velocity and a lane-changing prevention velocity. The stability condition of the model is derived and verified through numerical simulation, and impacts of several factors on stability are analyzed. The results display that the stability condition is consistent with the simulation results. The most significant factors impacting on the stability are the safe time-headway for lane-changing and the contribution proportion α of the safe velocity and lane-changing prevention velocity. The optimal values exist for the proportion α and lane-changing time headway that can make the stability of the traffic flow the highest.
Key words: Statistical and Nonlinear Physics
© EDP Sciences / Società Italiana di Fisica / Springer-Verlag GmbH Germany, part of Springer Nature, 2020