A Conflict Decision Model Based on Game Theory for Intelligent Vehicles at Urban Unsignalized Intersections

Xuemei Chen,Zijia Wang,Mengxi Li,Yangjiaxin Ou,Xuelong Zheng,Yufan Sun

doi:10.1109/access.2020.3031674

Xuemei Chen, Zijia Wang + Show 4 more

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https://doi.org/10.1109/access.2020.3031674

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Journal: IEEE Access	Publication Date: Jan 1, 2020
Citations: 16	License type: CC BY 4.0

Affiliation: Beijing Institute of Technology

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This article proposed a novel conflict decision model for intelligent vehicles based on game theory with analyzing the interaction behaviors between vehicles at urban unsignalized intersections. The proposed model can help intelligent vehicles cross intersections safely and more efficiently. Firstly, we developed an inference model for types of interactions among vehicles based on fuzzy logic. Then, the driving data was collected at urban unsignalized intersections by subgrade sensors and a retrofit intelligent vehicle and it was used in verifying the proposed inference model. After that, a conflict decision model considering safety, efficiency and comfort for intelligent vehicles based on game theory, was proposed to select the optimal driving strategies. Finally, a simulation and verification platform was built using Matlab/Simulink & Prescan. And the validity and effectiveness of the model were proved by simulation experiments. The results show the decision model can effectively help vehicles avoid conflicts and save their time spent in crossing intersections by 15 percent.

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Intelligent vehicles have drawn increasing attentions in recent years and many researchers have made great achievements about them
To overcome the problems mentioned above, This paper proposed a decision-making model based on game theory for intelligent vehicles to resolve conflicts, the contributions are listed as: (1) A decision-making model based on game theory for intelligent vehicles at urban unsignalized intersections is proposed with the considerations of driving safety, efficiency and comfort
A decision-making model based on game theory for intelligent vehicles is established to improve traffic efficiency at urban unsignalized intersections

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Intelligent vehicles have drawn increasing attentions in recent years and many researchers have made great achievements about them. Researchers have employed methods like gap acceptance model, conflict table algorithm and vector graph algorithm to solve the conflicts These models just explained the passing priorities of vehicles crossing the intersections, ignoring the interactions between intelligent vehicles and other traffic participants. Xiong [3,4] proposed a prediction method of driving intentions of surrounding vehicles based on HMM to realize the cooperative control among vehicles at intersections. In these researches, the accuracy of predicting drivers’ intentions is limited by the quality of the collected data and the decisionmaking process of vehicles has not been quantified

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