Advanced intersection management for connected vehicles using a multi-agent systems approach

Abstract

Transportation is responsible for approximately a third of greenhouse gases (GHG) and a major source of other pollutants including hydrocarbons (HC), carbon monoxide (CO), and oxides of nitrogen (NOx). Intelligent Transportation System (ITS) technology can be used to lower vehicle emissions and fuel consumption, in addition to reducing traffic congestion, smoothing traffic flow, and improving roadway safety. As wireless communication advances, connected-vehicles-based Advanced Traffic Management Systems (ATMS) have gained significant research interest due to their high potential. In this study, we examine the concept of ATMS for connected vehicles using a multi-agent systems approach, where both vehicle agents and an intersection management agent can take advantage of real-time traffic information exchange. This dynamic strategy allows an intersection management agent to receive state information from vehicle agents, reserve the associated intersection time-space occupancies, and then provide feedback to the vehicles. The vehicle agents then adjust their trajectories to meet their assigned time slot. Based on preliminary simulation experiments, the proposed strategy can significantly reduce fuel consumption and vehicle emissions compared to traditional signal control systems.