Proactive eco-friendly pheromone-based green vehicle routing for multi-agent systems.

Highlights • Greener aspects of routing were not well explored in recent pheromone schemes. • Eco-friendly Pheromone-based Green Vehicle Routing is proposed to reduce fuel burnt. • This is achieved by assigning paths with multiple green signalized intersections. • The proposed strategy can be implemented through a decentralized Multi-Agent system. Abstract The significant increase in vehicle numbers leads to adverse traffic congestion. Existing pheromone-based vehicle routing randomly assigns an alternative route to vehicles based on global distance and local pheromone intensity. Although urban congestion is reduced as vehicles are assigned paths with lower pheromone intensity, frequent stops due to numerous red signalized intersections within the paths can lead to high fuel consumption. To address this issue, a proactive Eco-friendly Pheromone-based Green Vehicle Routing (E-PGVR) strategy is proposed to prioritize the greener aspects of routing by reducing fuel consumption in addition to traffic congestion. First, paths with multiple green signalized intersections are assigned to increase the chance for vehicles to traverse multiple intersections with fewer stops, marking down fuel consumption. Second, the application of local dynamic information namely traffic light time, mean road speed, and predicted pheromone intensity encourages the implementation of a decentralized Hierarchical Multi-Agent Pheromone-based System (HMAPS). Third, a modified dynamic k-shortest path algorithm is proposed in the path assignment to reduce computational effort. Forth, Singapore traffic data that incorporates heterogeneous vehicle type is employed in the microscopic simulator (SUMO) to model real-world traffic scenario. Experiment results show that the proposed E-PGVR outperforms other approaches in reducing fuel consumption and CO 2 by 21.2%, mean waiting time by 30.0%, number of congested roads by 56.9%, mean travel time by 26.3%, and increasing number of arrived vehicles by 45.5%. [ABSTRACT FROM AUTHOR]