Coordinated Traffic Light Control in Cooperative Green Vehicle Routing for Pheromone-based Multi-Agent Systems

Abstract

Green transportation has been increasingly gaining attention in recent years. Existing pheromone-based traffic management frameworks were developed to reduce urban congestion by fusing traffic lights control strategies and vehicle routing schemes. Despite a significant reduction in traffic congestions, the greener aspects of transportation were not well investigated. In view of this, a Pheromone-based Green Transportation System (PGTS) is proposed to reduce Greenhouse Gas emissions and urban congestion in a three-step approach. First, traffic congestions are predicted based on the transport pheromone intensity of the target and adjacent upstream roads through an online epsilon-Support Vector Regression model. Second, a Coordinated Traffic Light Control (CTLC) strategy generates green wave scenario, dispersing heavy traffic on congested roads to the coordinated downstream paths. Third, a Cooperative Green Vehicle Routing (CGVR) takes a further leap by probabilistically rerouting upstream vehicles from entering the congested road, preventing the accumulation of vehicles that can lead to upstream congestion. Intuitively, the integration of CTLC and CGVR increases the chances that vehicles traversing multiple intersections with fewer frequencies of acceleration, effectively marking down fuel consumption. The proposed PGTS can be realized through a Pheromone-based Hierarchical Multi-Agent System (PHMAS). Based on Singapore traffic data, experimental results from a microscopic simulation SUMO show that the proposed PGTS outperforms other six approaches in reducing carbon dioxide emissions by 37.7%, fuel consumption by 37.6%, mean travel time by 47.5%, mean waiting time by 57.3%, and increasing number of arrived vehicles at designated destinations by 62.6%.