Development of AEB control strategy for autonomous vehicles on snow-asphalt joint pavement

Abstract

ABSRACT An autonomous emergency braking (AEB) algorithm for snow-asphalt joint pavement is proposed. Based on machine vision and kinetic analysis, we realize the identification of road information, including the road type, slope, and road section lengths. A new safety model, the reference velocity model, is proposed to solve the problem of determining the braking time on the joint pavement to achieve collision avoidance. In the asphalt section, we design the desired deceleration considering the comfort and safety, while in the snow section, we use the estimated maximum deceleration that the pavement can provide. To meet the desired deceleration requirement, we choose a single-neuron proportion integration differentiation (PID) controller with a Kalman filter. The joint simulation with CarSim and Simulink shows that the host vehicle successfully realizes collision avoidance in various working conditions and verifies the proposed AEB algorithm. Benefitting by the recognition of the forefront road conditions, our proposed model performs better than the traditional AEB model.