Lane-changing Model Based on Safety Potential Field Theory Under the Connected and Automated Vehicles Environment

To characterize the driving risks that vehicles face during the lane changing process in a future connected and automated vehicles (CAVs) environment effectively and ensure that vehicles make safer lane change decisions, a vehicle lane changing model based on the safe potential field theory was established in this study. First, the driving risk encountered during the vehicle lane changing process was evaluated and the potential distributions of the safety potential field under different motion states during the vehicle driving process were identified based on the potential field theory. Second, the critical distances between vehicles at the end of lane changing were summarized according to the distribution of different safety potential fields for relevant vehicles during the lane changing process. Unlike the traditional distance calculation model for vehicles, the method proposed in this paper can dynamically characterize the trends of the critical distance under different speed and acceleration conditions. According to these characteristics, various types of vehicle movement statuses can be perceived in real time in a CAVs environment. Additionally, the critical times required for lane changing under various motion states can be summarized and a model of the minimum safe distance for lane changing can be established based on the safety potential field theory. Numerical simulation analysis of the proposed model demonstrates that it can characterize the effects of various motion parameters on lane changing results. In a CAVs environment, will be perfected in the future, the proposed model can be further expanded to apply the distributions of the safety potential field to intervene in the vehicle lane changing process dynamically and perform vehicle group optimization control in real time. © 2021, Editorial Department of China Journal of Highway and Transport. All right reserved.