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.

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Existing traffic flow models give little consideration on vehicle sizes. We introduce the solid angle into car-following theory, taking the driver’s perception of the leading vehicle’s size into account. The solid angle and its change rate are applied as inputs to the novel model. A nonlinear stability analysis is performed to analyze the asymmetry of the model and the size effect of the leading vehicle, and the modified Korteweg–de Vries equation is derived. The solid angle model can explain complex traffic characteristics and provide an important basis for modeling nonlinear traffic phenomena.

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