Fuzzy-GSA Based Control Approach for Developing Adaptive Cruise Control

Abstract

Adaptive Cruise Control (ACC) controls vehicle speed and its distance to the proceeding vehicle in the same lane. In this paper a two-level control architecture is proposed to control both velocity and distance to the leading vehicle by taking advantage of fuzzy logic control (FLC) approach. Then the control parameters were tuned by Gravitational Search Algorithm (GSA) to ensure achieving the fastest and most accurate control response. To evaluate performance of the proposed scheme, a speed profile was developed in simulation based test platform to measure performance of the proposed ACC in different maneuvers including some velocity tests and a distance control maneuver. The results revealed that the proposed approach had a stable and fast response which satisfied the requirements of an ACC.