Role of ACO Driven AGV in Intelligent Transport Systems

Abstract

The cutting-edge evolution in the design of an Automated Guided Vehicle (AGV) has led to a tremendous transformation in the Intelligent Transport Systems (ITS). An organised fleet of AGVs may be deployed in order to optimize transportation times, augment the locomotion of the vehicles to reduce congestion, minimise the chances of collisions, efficient task and job scheduling programs, cooperative driving etc. To develop a solver for the aforementioned tasks, the requirement is that of a meta-heuristic technique that shall be able to handle the NP-hard problems efficiently. The Ant Colony Optimization (ACO) is one such probabilistic computational multi-agent mechanism that may be employed to accomplish the same. The paper focuses on the real-time applications of the ACO and its variants when combined with the AGVs for smart traffic management.