Modeling and analysis of car-following behavior considering backward-looking effect*

Abstract

The car-following behavior can be influenced by its driver’s backward-looking effect. Especially in traffic congestion, if vehicles adjust the headway by considering backward-looking effect, the stability of traffic flow can be enhanced. A model of car-following behavior considering backward-looking effect was built using visual information as a stimulus. The critical stability conditions were derived by linear and nonlinear stability analyses. The results of parameter sensitivity analysis indicate that the stability of traffic flow was enhanced by considering the backward-looking effect. The spatiotemporal evolution of traffic flow of different truck ratios and varying degrees of backward-looking effect was determined by numerical simulation. This study lays a foundation for exploring the complex feature of car-following behavior and making the intelligent network vehicles control rules more consistent with human driver habits.