Ant colony optimization-based traffic routing with intersection negotiation for connected vehicles

Abstract

This study presents a decentralized traffic management system that integrates dynamic traffic routing and signal-free intersection traffic control for connected vehicles (CV). In particular, we apply the ant colony optimization algorithm and the proposed concept of colored CV to solve the dynamic traffic routing problem with multi-source multi-destination traffic flows. Each CV, modeled as an ant, deposits pheromones on its path, while road sensors aggregate the pheromone information representing traffic conditions and transfer the information to the incoming CV to perform routing. Using the colored CV concept, the CV with the same destination deposit the corresponding pheromone called colored pheromone, and only these CV can interact with that pheromone. Thus, we can distinguish multi-source multi-destination traffic flows in the routing process. For implementing signal-free intersection traffic control, we propose a decentralized intersection negotiation protocol that allows the CV to pass the intersections by exchanging their trajectory information, thereby significantly reducing the time required by CV to pass the intersections. We performed extensive simulations to evaluate our system using Simulation of Urban Mobility, a microscopic traffic simulator. The results show improvement of our proposed system over the conventional traffic management systems in terms of the mean trip time and the number of running vehicles.