Optimization of Automatic Driving Path Planning in Probabilistic Roadmap Environment
Aiming at the specific scenario that the traditional probabilistic roadmap algorithm cannot meet the needs of safe driving of self-driving vehicles on slippery roads in rainy and snowy weather,a new probabilistic roadmap algorithm based on the probabilistic roadmap algorithm is proposed to optimise its configuration sampling and collision detection.A raster map is established based on the environment,and the traditional probabilistic roadmap algorithm is optimised,and distance detection is added to the configuration sampling and collision detection phases to control the sampling points and connecting edges away from the obstacles,so as to change the final undirected graph,avoid the dangerous situation of the vehicle advancing along the path close to the obstacles,and improve the safety of the vehicle travelling.Simulation results show that the algorithm can accurately select the path and achieve the expected results.
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