Advanced braking algorithm for robust longitudinal risk management

Abstract

This paper describes an advanced braking algorithm for robust longitudinal risk management to prevent or mitigate rear-end collisions. Since the proposed safety system works in conjunction with a human driver, the longitudinal safety system must be acceptable to the driver. The key to achieving this is to ensure that control signals are given at the appropriate time. In order to construct an suitable control system, a new longitudinal safety index was developed by using the time to collision and the warning index, which are well-known safety parameters in longitudinal safety control. The clearance and the relative velocity constitute essential signals for safety monitoring in longitudinal safety control. These measured sensor signals include the uncertainty in the measurement noise. To design a robust safety monitoring and control mode decision, information consisting of fusion of the measurement signals was obtained. In addition, an expected error range of the proposed safety index from the measurement noise can be defined from the covariance matrix of the Kalman filter and the deviation of the function of the new longitudinal safety index. The control performance of the proposed algorithm was evaluated by analysis of the simulation results. From this analysis, it can be concluded that the proposed advanced braking algorithm can substantially enhance the longitudinal safety and can guarantee a robust performance with respect to the sensor uncertainty.