Autonomous Obstacle Avoidance Control Strategy for Intelligent Vehicle Based on Lateral and Longitudinal Safety Distance Model

Obstacle avoidance decision is an important basis for path planning and the basic logic for establishing obstacle avoidance control methods. For the problems of the existing safety distance model's insufficient adaptability and single obstacle avoidance mode in complex traffic environments, an obstacle avoidance decision method based on lateral and longitudinal safety distance models is proposed. After establishing the longitudinal safety distance model which considers the road adhesion coefficient, the lane change safety distance interval model, the vehicle obstacle avoidance logic is designed. To constrain the vehicle obstacle avoidance deceleration, the peak adhesion coefficient is estimated by the Burckhardt tire model. The simulation results indicated that the method can effectively avoid vehicle collisions and enhanced the safety of driving.