Intelligent momentary assisted control for autonomous emergency braking

Abstract

Development of control algorithms for enhancing performance in safety-critical systems such as the Autonomous Emergency Braking (AEB) system is an important issue in the emerging field of automated electric vehicles. In this study, we model a safety distance-based hierarchical AEB control system constituted of a high-level Rule-Based Supervisory control module, an intermediate-level switching algorithm and a low-level control module. The Rule Based supervisor determines the required deceleration command that is fed to the low-level control module via the switching algorithm. In the low-level, two wheel slip control algorithms were developed, a Robust Sliding Mode control algorithm with an Artificial Neural Network (ANN) for nonlinear parameter estimation and a Gain-Scheduled Linear Quadratic Regulator. For the needs of this control design, a non-linear dynamic vehicle model was implemented whereas a constant tire-road friction coefficient was considered. The proposed control system was validated in Simulink, assuming a straight-line braking maneuver on a flat dry road. The simulation results demonstrated satisfactory emergency braking performance with full collision avoidance in both proposed control system combinations.