Optimal Management and Configuration Methods for Automobile Cruise Control Systems

Autonomous systems incorporate varying degrees of adaptation behavior to sustain their operations with acceptable quality of service (QoS). The QoS capability of such highly complex dynamic adaptive systems depends on how well they respond to hostile external events. The paper formulates model-based assessment techniques to benchmark the QoS capability of a networked system of cars S. We elaborate on this approach with a MATLAB-SIMULINK-based case study of adaptive cruise control (ACC) system in automobiles: first, for in-vehicle CC and then for multi-vehicle coordinated ACC. We employ model-predictive intelligent control methods to dynamically adapt the ACC system configurations to attain optimal behavior.