对于智能车辆高速主动避撞,目前的研究大多没有着重考虑车辆动力学模型,这直接限制了避撞算法在实际应用的安全性.为此基于前方相邻车辆的预测轨迹和自车动力学稳定性,提出一种基于前车轨迹预测的智能车辆高速主动避撞改进方法.基于下一代交通仿真(Next generation simulation,NGSIM)数据集进行数据处理与特征提取;搭建长短期记忆循环神经网络(Long short-term memory-recurrent neural network,LSTM-RNN)预测模型并进行训练、预测和验证,得到前车多时域预测轨迹;根据前车预测轨迹和自车动力学稳定性,设计合理的主动换道避撞策略.基于优劣解距离(Technique for order preference by similarity to ideal solution,TOPSIS)算法规划出具备安全性的主动避撞路径;搭建Prescan-Simulink-Carsim硬件在环试验平台,对提出的主动避撞方法进行试验验证,结果表明该方法可有效解决高速场景下的避撞安全性问题.
Active Collision Avoidance Method of Intelligent Vehicles Based on the Trajectory Prediction of Front Vehicles in High-speed Scene
For the intelligent vehicle active collision avoidance at high speed,most of the current studies do not focus on the vehicle dynamics model,which directly limits the safety of the collision avoidance algorithm in practical application.Therefore,an improved method for intelligent vehicle high-speed active collision avoidance based on the predicted trajectory of adjacent vehicles in front and the stability of self vehicle dynamics is proposed.Data processing and feature extraction are carried out based on the Next generation simulation(NGSIM)data set.The prediction model of the Long short-term memory-recurrent neural network(LSTM-RNN)has been established and trained,prediction and validation have been carried out to obtain the multi-time domain prediction track of the preceding vehicle.According to the predicted trajectory and the dynamic stability of the preceding vehicle,a reasonable method of active lane changing and obstacle avoidance is designed.Based on Technique for order preference by similarity to ideal solution(TOPSIS)algorithm,an active collision avoidance path with safety is planned.The Prescan-Simulink-Carsim hardware-in-the-loop test platform is built to verify the proposed active collision avoidance method,and the results show that the proposed method can effectively solve the problem of collision avoidance safety in high-speed scenarios.
intelligent vehiclescollision avoidance in high-speed scenetrajectory predictiondynamic stabilityhardware-in-the-loop
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