首页|The Traffic Safety Assessment Model for Mixed Urban Traffic Based on Driving Safety Field and ICVs
The Traffic Safety Assessment Model for Mixed Urban Traffic Based on Driving Safety Field and ICVs
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NETL
NSTL
Wiley
To accurately assess the driving risks associated with mixed traffic scenarios in urban areas and align with the direction of Internetof Things (IoT) technologies. An intelligent connectivity traffic safety assessment model for mixed urban traffic based on the ICVsis proposed. First, this paper proposes the traffic safety assessment model based on the driving safety field, the model integratespotential, kinetic, and behavior fields. In the process of establishing the mode, we have incorporated the acceleration parameterto dynamically capture driving risk trends. Subsequently, we define a mixed traffic scenario and calculate the driving risks forroad users under different driving states based on this algorithm. The results demonstrate that the model effectively captures thedriving risks of road users in different states, and the evaluation outcomes align with real-world situations, thereby validatingits effectiveness. The significance of this research lies in providing a theoretical foundation for the application of the Internet ofThings (IoT) in complex traffic scenarios and supporting future route planning and driving safety decision-making in intelligenttransportation systems. Additionally, this model presents new ideas and methods for the development and application of ICVstechnology, contributing to the advancement of intelligent transportation systems.
internet of thingslearning algorithmmixed trafficsafety field theorytraffic factorstraffic safety assessment model
Renjie Wang、Jing Cheng
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Department of College of Architecture and Engineering, Tongling University, Tongling, China
Department of College of Business Administration, TonglingUniversity, Tongling, China
NETL
NSTL
Wiley
