An improved car-following model considering the space relaxation effect

• Published in: Physica A 2025-02, Vol.660, p.130357, Article 130357
• Main Authors: Liu, Zhaolun, Yan, Maode, Zuo, Lei
• Format: Article
• Language: English
• Subjects: Car-following model; Data similarity analysis; Full velocity difference model; Space relaxation effect; Stability analysis
• ISSN: 0378-4371
• DOI: 10.1016/j.physa.2025.130357

Gap between car-following(CF) models and real traffic system is a tough question, which directly affects the accuracy on describing traffic evolution. In general, the sensitivity parameter of CF models is considered as a constant. However in real traffic system, when the space between two successive vehicles is sufficiently large, the following vehicle is insensitive to space variation. To fill this gap, the space relaxation effect is explored and expressed in this paper. Firstly, data segments which record acceleration, velocity difference(VD) and space headway dearvation(SHD) from steady-state to unsteady-state are extracted from next generation simulation(NGSIM) dataset. By employing the discrete Fréchet distance(DFD) algorithm, the similarity of temporal curves in each data segment is analyzed so that the space relaxation effect is explored. Base on this fact, an improved CF model is proposed and liner stability of model is strictly analyzed. Then, numerical simulations are carried out. Following vehicles’ acceleration, space headway(SH), velocity are exhibited and analysed in detail. Comparing with full velocity difference model(FVDM), our improved model can express a smoother acceleration adjustment process of subject vehicle under relatively large SH. Finally, 50 times data fitting exprements are conducted. Actual velocity and trajectory of following vehicle in every instant is compared with the values that computed by FVDM and our imroved models respectively. The results reveal that space relaxation effect is actually existent in real traffic system. Our improved model can accurately depict the traffic evolution by considering this effect. •Data segments are extracted from public dataset, which describes the vehicle kinetic properties under disturbance.•Space relaxation effect is revealed by analysing major factors of data segments.•An improved car-following model considering the space relaxation effect is proposed.