Swarm intelligence-based green optimization framework for sustainable transportation

Abstract

Traffic congestion is one of the most critical issues in developing sustainable transportation in smart cities. As the Internet of Things evolves, connected vehicle technology has arisen as an essential research topic in smart, sustainable transportation. This study investigates a decentralized green traffic optimization framework by pushing swarm intelligence into connected vehicles to mitigate traffic congestion. We present a dynamic traffic routing method based on ant species’ swarm intelligence for connected vehicles so that they can communicate with each other and their surrounding environment via digital pheromones to perform routing decision-making in a decentralized manner. Traditional pheromones attract other vehicles to move to the optimal path, which will soon be congested if many vehicles travel on that path concurrently. To overcome this limitation, we propose the concept of repelling pheromone, which generates a repulsive force among vehicles so that their travel paths are distributed throughout a road network, resulting in a congestion-free road network. The proposed method is validated in the Simulation of Urban Mobility platform. Simulation findings reveal that the proposed method outperforms baseline methods in mitigating traffic congestion, reducing average fuel consumption and emissions by 13–19% and the average trip duration by 19–28%.