Multi-anticipative bi-directional visual field traffic flow models in the connected vehicle environment

Abstract

In the connected vehicle environment, a vehicle can obtain the information of multiple front and rear vehicles. This driving strategy of bi-directional visual field and multiple anticipation can be implemented to traffic flow modeling. In this paper, an extended car-following model with consideration of bi-directional visual field and multiple anticipation is proposed. A novel macroscopic traffic flow model is developed based on the relationship between the microscopic and macroscopic variables, and the validity of the model is confirmed through the theoretical and numerical studies. The stability analysis shows that the multiple anticipation can improve the stability of traffic flow, and the results of numerical simulation illustrates that the new model can reproduce the local clustering phenomenon of traffic flow.