首页|Intelligent momentary assisted control for autonomous emergency braking
Intelligent momentary assisted control for autonomous emergency braking
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NSTL
Elsevier
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.
AEBBraking safety distanceModelling and simulationArtificial intelligenceSliding modeLyapunov stabilityOptimal controlGain schedulingMATLAB/Simulink
Nick Bassiliades、Konstantinos Gounis
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School of Informatics, Aristotle University of Thessaloniki
NSTL
Elsevier
