Research on curve braking based on sensor fusion

The stability of the braking process of the intelligent vehicle is mainly divided into two parts: the accurate selection of the braking target and the stability during a braking on curve. For the selection of braking targets, this paper uses sensor fusion to identify and fit lane lines, and establishes a road curvature estimation model, which is used to identify the target vehicle in front of the lane, thereby effectively reducing vehicle mis-braking. The emergency braking of a vehicle in a curve is prone to instability. To solve this problem, a sliding-mode controller is worked out based on the joint control of the yaw rate and the side slip angle, in order to calculate the additional yaw moment. Then the additional yaw moment is converted into the braking moment of the wheels, so as to realize that the actual yaw rate and the side slip angle of the center of mass can follow the ideal value well. Finally, using Prescan, Carsim and MATLAB/Simulink for joint simulation, the results show that the proposed target vehicle recognition strategy based on sensor fusion can effectively reduce the vehicle’s mis-braking on curve, and after the torque is distributed through the designed sliding mode controller, it can effectively improve the braking stability of the vehicle.