To improve intelligent vehicle drive performance and avoid vehicle side-slip during target path tracking, a linearized four-wheel vehicle model is adopted as a predictive control model, and an intelligent vehicle target path tracking method based on a competitive cooperative game is proposed. The design variables are divided into different strategic spaces owned by each player by calculating the affecting factors of the design variables with objective functions and fuzzy clustering. Based on the competitive cooperative game model, each game player takes its payoff as a mono-objective to optimize its own strategic space and obtain the best strategy to deal with others. The best strategies were combined into the game strategy set. Considering the front wheel angle and side slip angle increment constraint, tire side-slip angle, and tire side slip deflection dynamics, it took the path tracking state model was used as the objective, function and the calculation was validated by competitive cooperative game theory. The results demonstrated the effectiveness of the proposed algorithm. The experimental results show that this method can track an intelligent vehicle quickly and steadily and has good real-time performance.
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