Design of adaptive cruise control system based on fuzzy logic using genetic algorithm

Abstract

Adaptive Cruise Control system provides significantly enhanced driver convenience and reduced workload as a driver assistance system. Feature of ACC system is adaptation to a target speed and speed reduction to keep a safe distance from preceding vehicle. But conventional ACC systems control only throttle and don’t manage speeds under 30km/h and are not useful in traffic jam or urban driving. So, the current focus of research into ACC systems is on augmenting the ACC systems with `Stop and Go` capabilities. Recently, new approaches applied intelligent control techniques, such as fuzzy logic control have been tried for ACC systems to solve problems of conventional ACC systems. But existing fuzzy logic based ACC systems are designed without considering driving comfort, throttle and brake input oscillations and fuel efficiency. In this paper, new fuzzy ACC controller with `Stop and Go` capabilities using Genetic Algorithm(GA) is proposed. Driving comfort, throttle and brake input oscillations and fuel efficiency as well as safe inter-vehicle distance are considered through defining proper fitness function. Experiments using Carsim(Vehicle simulation program of Mechanical Simulation Coporation) are carried out in the `Stop and Go` simulation scenario to evaluate proposed fuzzy ACC controller.