Intelligent Vehicle Lane Changing Path Planning Based on Predictive Risk Field Model
In view of complex driving environments and expression methods of intelligent vehicles,a predictive risk field model for intelligent vehicles incorporating long short term memory(LSTM)predic-tion model was proposed.Based on the traditional potential field model,the predictive information about dynamic target behaviors was considered,and the kinetic energy field of dynamic prediction was established.In addition,the kinetic energy field was superimposed with the risk field of other risk ele-ments in the road environment to construct a unified model,namely the predictive risk field.By design-ing the cost function of the risk field,the minimum cost evaluation of the planning trajectory cluster was completed,and the optimal path planning trajectory was obtained.In order to verify the effectiveness of the method,joint simulations and real-vehicle verification were conducted.The experimental results show that the predictive risk field model effectively expresses the traffic situation in the complex driving environment,and the selected optimal paths improve comprehensive safety.
path planningtrajectory predictionLSTMpredicted risk field
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