Intelligent momentary assisted control for autonomous emergency braking

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