Capturing the Impacts of Multi-Source Information under the V2X Environment Based on the Car-Following Model
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This study aims to establish an improved model framework for integrating the car-following information under the V2X environment and compare the contributions of various information. Based on the vehicle interaction information identified in the V2X environment, the improved model is established by integrating multi-source information, which includes preceding and following car position, velocity difference, accelerations of multiple preceding vehicles, adjacent vehicle optimal velocity difference and driver memory effect information, named BL-MSIF model. Then numerical simulation is used to validate the BL-MSIF model. The results indicate that the BL-MSIF model has excellent characteristics in enhancing traffic flow stability. In addition, based on numerical simulations, a comparative analysis of the contributions of various types of information in the BL-MSIF model is conducted from perspectives of traffic flow stability, additional energy consumption and traffic safety. It is found that the acceleration information of preceding vehicles holds the highest importance, while the contribution of driver memory effect information to the model is relatively low. The results of this study serve as a crucial benchmark for the practice and theory related to traffic flow in the V2X environment.
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Copyright (c) 2026 Qing WANG, Meiying JIAN, Pengrui ZHAO, Qianwei NIU, Chengbing LI
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