Development of an Agent-Based Online Adaptive Signal Control Strategy Using Connected Vehicle Technology

For arterial roadways, most Active Traffic and Demand Management (ATDM) strategies focus on traffic signal timing optimization at signalized intersections. A critical drawback of conventional traffic signal control strategies is that they rely on measurements from point detection, and estimate traffic states such as queue length based on very limited information. The introduction of Connected Vehicle (CV) technology can potentially address the limitations of point detection via wireless communications to assist signal phase and timing optimization. In this paper, we develop an agent-based online adaptive signal control (ASC) strategy based on real-time traffic information available from CV technology. We then evaluate the proposed strategy in terms of travel delay and fuel consumption, relative to a Highway Capacity Manual (HCM) based method in which hourly traffic demand is assumed to be known accurately a priori. Study results indicate that the proposed strategy outperforms the HCM based method and is very robust to the traffic demand variations.