Design and Simulation of Intelligent Vehicle Path Planning Program Based on High-stakes Betting Algorithm

This study, with the background of solving the problem of intelligent vehicles finding and planning the optimal path on their own in a complex maze environment, innovatively proposes a high-gambling algorithm, builds a minimum MCN system with STM32 microcontroller as the control core, and combines modules such as motor drive, infrared sensing, gyroscope steering and human-machine interaction. The program is written using Keil5. The path planning program for the intelligent vehicle was designed and simulated using Update Auto. The program was constructed to implement functions such as path planning, intelligent obstacle avoidance, and human-machine interaction, and then the path planning system was improved by the optimization method, which increased the response time and search efficiency. Comparative simulation experiments were conducted based on different algorithms and target locations, and different control electrical signals were generated based on the results to complete the path planning function of the intelligent vehicle and verify the feasibility of the algorithm.