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Intelligent Vehicle Trajectory Tracking and Identification Technology Based on Multi-Fitness Genetic Algorithm

Track control is an important technology of intelligent vehicle control. The purpose of track control system is to make it possible by controlling the speed and direction of the vehicle under the premise of satisfying certain comfort, safety and stability. The purpose of this paper is to study the intelligent vehicle trajectory tracking (IVTT) and recognition technology based on multi-fitness genetic algorithm (GA). This paper analyzes the GA and the characteristics of the GA, and analyzes the vehicle model and the experimental simulation design, and draws the experimental results. The empirical analysis results show that the multi-fitness GA uses rolling, optimization and feedback correction, and the solution results are used for intelligent car control, with good real-time performance. The algorithm is verified by hardware-in-the-loop simulation test, which shows that the algorithm has good performance, has stable and accurate tracking ability for the tracked trajectory, and has sufficient real-time performance. After adopting the multi-fitness GA, the performance of the traditional IVTT and identification technology has been greatly improved, and we conducted a questionnaire and found that more than 88% of the people felt that the design of the IVTT and identification technology used multi-adaptability GA, found that the design efficiency has become high.