The Traffic Safety Assessment Model for Mixed Urban Traffic Based on Driving Safety Field and ICVs

Abstract

To accurately assess the driving risks associated with mixed traffic scenarios in urban areas and align with the direction of Internet of Things (IoT) technologies. An intelligent connectivity traffic safety assessment model for mixed urban traffic based on the ICVs is proposed. First, this paper proposes the traffic safety assessment model based on the driving safety field, the model integrates potential, kinetic, and behavior fields. In the process of establishing the mode, we have incorporated the acceleration parameter to dynamically capture driving risk trends. Subsequently, we define a mixed traffic scenario and calculate the driving risks for road users under different driving states based on this algorithm. The results demonstrate that the model effectively captures the driving risks of road users in different states, and the evaluation outcomes align with real-world situations, thereby validating its effectiveness. The significance of this research lies in providing a theoretical foundation for the application of the Internet of Things (IoT) in complex traffic scenarios and supporting future route planning and driving safety decision-making in intelligent transportation systems. Additionally, this model presents new ideas and methods for the development and application of ICVs technology, contributing to the advancement of intelligent transportation systems.