Abstract:In view of the imperfection of road potential field when the traditional artificial potential field method was applied in driverless vehicle path planning, an improved artificial potential field model was proposed to obtain the obstacle avoidance trajectory. Firstly, combined with the change of potential energy in the road, the gravitational potential field was improved; the elliptical repulsion potential field was increased to replace the traditional repulsion potential field; the road boundary repulsion potential field was increased to ensure that the vehicle would not drive out of the boundary; the speed potential field of obstacles was increased to improve the rationality of the obstacle. At the same time, a three-degree-of-freedom vehicle dynamics model was established, and the model predictive control algorithm was used for tracking control. The research results show that the improved artificial potential has a good obstacle avoidance path planning, and meets the dynamic constraints in all aspects at the same time. The rotation angle change is within ±3°, and the maximum lateral acceleration is 4.54 m/s2<0.67 μg, which ensures the driving stability and comfort of the planned path.
李军,李古月. 基于改进人工势场的路径规划与跟踪控制[J]. 重庆交通大学学报(自然科学版), 2020, 39(09): 25-30.
LI Jun, LI Guyue. Path Planning and Tracking Control Based on
Improved Artificial Potential Field. Journal of Chongqing Jiaotong University(Natural Science), 2020, 39(09): 25-30.
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