考虑道路附着系数的智能车辆主动避撞OA

To improve the effectiveness of the active collision avoidance strategy,a risk assessment method for colli-sion time margin was proposed.The three-degree-of-freedom vehicle model and the Dugoff tire model were estab-lished,and the state parameters were calculated to obtain the normalized tire force.The pavement adhesion coeffi-cient estimator was designed based on the traceless Kalman filtering algorithm,and the effectiveness of the adhesion coefficient estimator was verified through simulation.The road adhesion coefficient was added to the safety distance model to address the limitations of the traditional collision avoidance model,which only considered the position and the vehicle movement conditions.The active collision avoidance path was generated by using a fivetic polynomial,and the required safe steering distance was calculated.Based on the risk assessment method,a collision avoidance mode selection strategy was designed,enabling intelligent vehicles to select the appropriate collision avoidance mode according to the kinematic relationship with obstacles.The longitudinal control based on the vehicle inverse dynamic model and the lateral control using MPC were adopted to decouple the control of intelligent vehicles.The effectiveness of the collision avoidance strategy was verified through the joint simulation experiment of Carsim and Simulink and the real vehicle test.