Research of car-following behavior is very important to alleviate traffic congestion and ensure traffic safety. To describe the car-following behavior of connected vehicles and restore the real driving environment, this paper presents an improved car-following model for connected vehicles by considering driver characteristic and speed information of multiple vehicles, which reflects the interaction between adjacent connected vehicles and the influence of driver characteristic on the stability of car-following. The linear stability analysis and nonlinear stability analysis prove that the improved model is effective and can promote the stability of traffic flow more than other models. In addition, the numerical simulations show that the new model performs better in eliminating disturbances than other models. Finally, the parameters of proposed model are calibrated based on NGSIM data. The results show that the new model performs well in car-following process, keeping a safe distance from the leader vehicle without sudden acceleration and deceleration. The new model also can predict the acceleration behavior of the leader vehicle after emergency brake. In summary, the model proposed in this paper can be used as active safety technology to prevent collision accidents, or as a user-defined function or model in the traffic simulation software, or as car-following strategy in driverless algorithms.


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    Title :

    Modeling and stability analysis of car-following behavior for connected vehicles by considering driver characteristic


    Contributors:


    Publication date :

    2024-05-01




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





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