Modeling the heterogeneous traffic flow considering the effect of self-stabilizing and autonomous vehicles
Yuan Gong, Wenxing Zhu
Abstract
With the increasing maturity of automatic driving technology, the homogeneous traffic flow will gradually evolve into the heterogeneous traffic flow, which consists of human-driving and autonomous vehicles. To better study the characteristics of the heterogeneous traffic system, this paper proposes a new car-following model for autonomous vehicles and heterogeneous traffic flow, which considers the self-stabilizing effect of vehicles. Through linear and nonlinear methods, this paper deduces and analyzes the stability of such a car-following model with the self-stabilizing effect. Finally, the model is verified by numerical simulation. Numerical results show that the self-stabilizing effect can make the heterogeneous traffic flow more stable, and that increasing the self-stabilizing coefficient or historical time length can strengthen the stability of heterogeneous traffic flow and alleviate traffic congestion effectively. In addition, the heterogeneous traffic flow can also be stabilized with a higher proportion of autonomous vehicles.