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Modeling car-following behavior in heterogeneous traffic mixing human-driven, automated and connected vehicles: considering multitype vehicle interactions

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Abstract

In this study, a car-following model is put forth to explain the car-following behavior of HDVs (human-driven vehicles), AVs (autonomous vehicles) and CAVs (connected and automated vehicles) in mixed traffic. Based on the IDM (intelligent-driver model) and molecular dynamic theory, the model includes the velocity of surrounding vehicles along with the difference of velocity and the headway between each pair of vehicles. The drivers’ sensitivity to the deceleration of the nearest front vehicle was considered in HDV car-following modeling and the influences of various kinds of nearest front and rear vehicles were distinguished in the CAV model. Based on the information obtained from the real road test mixed with HDVs, AVs and CAVs, the optimum value of the model parameters was obtained and the accuracy of model was verified with simulation. The results show that the simulation for HDVs’, AVs’ and CAVs’ car-following behavior under the proposed model is more accurate than that for the IDM, ACC (adaptive cruise control) model and CACC (cooperative adaptive cruise control) model. The model can be applied to car-following simulations of HDVs, AVs and CAVs in mixed traffic, in the model the tools and concepts of nonlinear dynamics especially molecular dynamic theory is applied which can benefit road traffic vehicle interaction analysis. In addition, this study provides valuable suggestions and guidance for effectively guiding AVs and CAVs to follow vehicles and improving the stability of car-following behavior.

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The data supporting the conclusions of this article are available from the corresponding author on reasonable request.

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Acknowledgements

This work is supported by the NSFC of China under Grant U1864206.

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  1. State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun, 130022, Jilin, China

    Ziyu Song & Haitao Ding

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  1. Ziyu Song
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  2. Haitao Ding
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Song, Z., Ding, H. Modeling car-following behavior in heterogeneous traffic mixing human-driven, automated and connected vehicles: considering multitype vehicle interactions. Nonlinear Dyn 111, 11115–11134 (2023). https://doi.org/10.1007/s11071-023-08377-y

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