Adaptive Stanley Control Method Based on Dynamic Window Approach

Stanley algorithm is a classical algorithm in automatic driving path tracking algorithm, which has the advantages of low computational complexity and good tracking effect. However, the tracking accuracy of the traditional Stanley algorithm is limited by the gain parameters and the gain coefficients cannot be dynamically adjusted according to the road conditions. To improve the tracking accuracy and driving stability, an adaptive Stanley control algorithm based on DWA (DWA-Stanley) is proposed, which is used to sampling the velocity vector space and selecting the evaluation function, the vehicle motion planning is based on the best set of velocity values. In this paper, the DWA-Stanley algorithm is validated based on three different driving speeds. Simulation results show that an racecar using the DWA-Stanley algorithm has higher tracking accuracy and smoothness than a conventional Stanley.