CV-MMP: max-pressure control for multi-modal traffic in partially connected vehicle environments

Abstract

Among real-time traffic control methods, max-pressure (MP) control stands out due to its simplicity, decentralized nature, and robust theoretical foundation. Besides, advancements in connected vehicle (CV) technology have motivated a significant amount of research into traffic signal control based on CVs. Nevertheless, few studies have been dedicated to MP control in partially CV environments and meanwhile consider multi-modal traffic flows. To fill this research gap, this study proposes CV-based multi-modal MP control (CV-MMP), which calculates the pressure based on travel time information of CVs weighted by vehicle occupancy. Therefore, a hierarchical multi-modal traffic signal priority controller is achieved in a soft manner. Besides, adapting to the requirements of practical applications, CV-MMP is extended to fuse detector data and consider phase switching lost time and cyclic phase sequence. The evaluation results based on a toy network simulation demonstrate that CV-MMP can significantly reduce transit delay with a small increase in private vehicle delay, resulting in a significant reduction in average person delay. In addition, approximately 75% of CBs pass through the network without experiencing delays due to stopping. Therefore, our method can achieve effective transit signal priority and even transit signal coordination under single transit requests.