Modeling and Simulation of Autonomous Vehicle Management System Using Fuzzy Theory

Abstract

ABSTRACT 

Fuzzy techniques have demonstrated a surge in the practical applications of fuzzy set theory. This paper presents the speed control mechanism that solves the problem intelligently by learning, adaptation and incorporating human knowledge. The proposed speed controller is used to manage the speed of the trains while at the same time managing the uncertainty in the condition of railway tracks. To deal with the aforesaid issues of uncertainty a Fuzzy Inference System has been proposed. This helps in maintaining the optimum speed of railway vehicles, based on some rules derived from expert knowledge. The proposed system has been aided by some active agents such as environment monitoring and time scheduling that minimizes the risk of undesired circumstances. This paper presents the simulated form of a vehicle control system, which is controlling speed by controlling vehicle deviation index, channelizing the traffic and maintaining track condition. Designing of Fuzzy Inference Systems for this speed controller is based on fuzzy set theory and it requires the computation to be carried out in real time.

Keywords: Fuzzy systems, modeling and simulation, speed control system, environment conditions, fuzzy inference system, clustering, speed scheduling, time scheduling, train management system, speed scheduling