Intelligent Vehicle Lane Change Collision Avoidance System Based on the Safe Boundary of Trajectory Prediction

doi:10.3901/JME.2024.10.317

Abstract

Abstract: The uncertainty of trajectory prediction will lead to SOTIF risks of lane change collision avoidance(LCCA) system. To deal with it, a LCCA control method based on the safe boundary of trajectory prediction is proposed for intelligent vehicle. First, the uncertainty of the cut-in trajectory of the front vehicle is quantified by Chebyshey interval analysis method, and the formula of trajectory prediction safe boundary is constructed. On this basis, the collision risk analysis of lane change is carried out, and the vehicle lane change safe boundary in the process of lane change is determined. Then, with the lane change safe boundary as the constraint, a lane change controller based on Tube-RMPC is designed to realize active LCCA control of self-vehicle. The effectiveness of the proposed method is evaluated in Carsim/Simulink by comparing with ordinary LCCA system that does not account for prediction uncertainty. The safety of the system is further verified via the hardware-in-the-loop experiment. The results show that the obtained trajectory prediction safe boundary can effectively envelop the cut-in trajectories of the front vehicle and improve SOTIF of the LCCA system.

Key words: trajectory prediction uncertainty, SOTIF, lane change collision avoidance system, safe boundary, interval analysis

CLC Number:

TG156

TAN Dongkui, HU Gangjun, ZHU Bo, HU Xudong, YAO Mingyao. Intelligent Vehicle Lane Change Collision Avoidance System Based on the Safe Boundary of Trajectory Prediction[J]. Journal of Mechanical Engineering, 2024, 60(10): 317-328.

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