Multi-Agent Intersection Management for Connected Vehicles Using an Optimal Scheduling Approach

Abstract

Today's transportation systems are facing numerous issues resulting from the increased travel demands and limited capacities of roadway infrastructure. As a potential intelligent transportation system (ITS) solution, multi-agent intersection management systems have recently received increased attention with the rapid advance in wireless communications and comprehensive vehicular technologies. Most of the proposed multi-agent system approaches take a FIFO (first-in first-out) approach to time-space occupancy scheduling. However, by also optimizing the departure sequence, greater global benefits are possible. In this paper, we propose a modified multi-agent system with optimal scheduling of Vehicle Agent's (VAs') departure times. Compared with the FIFO-based system developed in the authors' previous work, the modified system can provide more system-wide benefits in terms of mobility, reliability and sustainability. Simulation studies have shown improvements in travel times, but more importantly an approximately 58% reduction in travel time variability and 49%-60% reductions in (partial) stops. These leads to potential benefits in fuel consumption and pollutant emissions, primarily by carefully designing VAs' trajectories through the intersection.