Analyzing the Collision Probability of Autonomous Vehicle at Crossroad

It is essential to assess the autonomous vehicle operation safety during driving, which can avoid or reduce the collision risk by evaluating the drive safety. In this paper, a collision risk assessment algorithm is proposed, that is quantifies the auto-drive vehicle collision risk by the Time to Collision (TTC) frequency. Firstly, the Long Short Time Memory network (LSTM) is used to predict the surrounding vehicle trajectory; Moreover, the collision point between the auto-drive vehicle and the surrounding vehicle is determined, and the frequency distribution result of TTC is calculated by the Monte Carlo simulation method; Finally, the running speed & hazard probability is obtained by changing the running speed of auto-drive vehicle, and the running speed & safety probability is obtained further. It can be seen from the result that the proposed method can provide an effective evidence for decision-making layer of auto-drive vehicle, improve the running safety of vehicle, and reduce the operation risk of auto-drive vehicle.