ACO-based Approach on Dynamic MSMD Routing in IoV Environment

Abstract

Recently, the advance of the Internet of Things (IoT) and wireless communication technology, specifically Vehicles-to-Everything (V2X), makes a huge contribution to road transportation. The fully connected and autonomous system of road transportation can be basically made in practice by integrating V2X with a current autonomous vehicle. In this paper, we focus on dynamic traffic routing for IoT-based connected vehicles. First, we define the problem of identifying the best paths for all vehicles with different sources and different destinations, or multi-source multi-destination (MSMD) traffic flows. Then, Ant Colony Optimization (ACO)-based approach with coloring ants concept is proposed to solve the problem in a decentralized and self decision-making manner. The simulation is carried out on the NetLogo platform with a multi-intersection scenario. The simulation results show that the ACO-based routing approach outperforms the non-ACO-based approach in terms of average traveling time and the number of vehicles passing metrics.