Fuzzy Decision Support in Distributed V2V Systems

Abstract

This paper presents a new approach of automated decision making in vehicle-to-vehicle (V2V) environments. Approach is based on extension of fuzzy knowledge-based decision making with automatic V2V communication that provides an ability for systems of Intelligent Transportation Agents (ITAs) to create a distributed network, where each agent is a part of the coalition that reacts to the environment changes (such as traffic jams, car accidents etc.). This paper considers a particular task of finding the shortest path in dynamical environments. An architecture of the system as well as mathematical model and simulation results is presented in the paper.