Vehicle path planning in high-density traffic scenarios during large-scale sports events

This study proposes a vehicle path planning method for high-density traffic scenarios during large-scale sports events. Firstly, a road network cloud grid structure model is constructed, which combines factors such as traffic road design characteristics, dynamic characteristics, and impedance to provide a foundation for vehicle path planning in high-density traffic scenarios. Secondly, using complex network models and road impedance theory, a traffic congestion network model is constructed to accurately extract congestion information in high-density traffic environments. Finally, a composite field model of repulsive force is constructed, combined with vehicle speed adjustment strategies, to achieve dynamic obstacle avoidance path planning and real-time updates for vehicles in high-density traffic scenarios. The experimental results show that under the same testing environment, the congestion delay time of our method is only 20 minutes, and the path length is shortened by about 7-10km.