基于时空风险的智能驾驶车辆避险决策规划

In order to improve the collision risk assessment method of intelligent driving vehicles in complex road scenarios to generate effective risk avoidance trajectories in real time，in this paper a risk avoidance decision planning method for intelligent driving vehicles based on spatiotemporal risk is proposed. Firstly，the multi-domain risk measurement of time-space coupling is used as the evaluation index to supervise the horizontal and longitudinal collision risk of intelligent driving vehicles. At the same time，the change of driving risk index is monitored in real time. Through the correlation analysis with the risk database of typical risk avoidance scenarios，potential collision risk is judged，so as to avoid the risk in advance. Then，according to the driving risk field，the uneven sampling of the vehicle target state is carried out to avoid the driving area with high driving risk and improve the safety and real-time performance of the risk avoidance planning. The experimental results show that the proposed risk avoidance decision planning method can safely and effectively avoid the risk of horizontal and longitudinal collision，which can detect the potential collision risk 0.5 s in advance according to the time domain correlation analysis of the risk index，so as to avoid the risk smoothly in advance. The average planning time of the risk avoidance trajectory can be shortened from 0.13 to 0.07 s by uneven sampling.