Max-Pressure Controller for Traffic Networks Considering the Phase Switching Loss

Efficient traffic signal control plays a critical role in promoting sustainable mobility by reducing congestion and minimizing vehicle emissions. This paper proposes an enhanced max-pressure (MP) signal control strategy that explicitly accounts for phase switching time losses in grid road networks. While the traditional MP control strategy is recognized for its decentralized architecture and simplicity, it often neglects the delays introduced by frequent phase changes, limiting its real-world effectiveness. To address this issue, three key improvements are introduced in this study. First, a redefined phase pressure formulation is presented, which incorporates imbalances in traffic demand across multiple inlet roads within a single phase. Second, a dynamic green phase extension mechanism is developed, which adjusts phase durations in real time based on queue lengths to improve traffic flow responsiveness. Third, a current-phase protection mechanism is implemented by applying an amplification factor to the current-phase pressure calculations, thereby mitigating unnecessary phase switching. Simulation results using SUMO on a grid network demonstrate that the proposed strategy significantly reduces average vehicle delays and queue lengths compared with traditional MP, travel-time based MP, and fixed-time control strategies, leading to improved overall traffic efficiency. Specifically, the proposed method reduces total delay by 24.83%, 26.67%, and 47.11%, and average delay by approximately 16.18%, 18.91%, and 36.22%, respectively, while improving traffic throughput by 2.25%, 2.76%, and 5.84%. These improvements directly contribute to reducing traffic congestion, fuel consumption, and greenhouse gas emissions, thereby reinforcing the role of adaptive signal control in achieving smart and sustainable cities. The proposed approach can serve as a practical reference for improving real-world traffic signal control systems, particularly in regions seeking to improve sustainability and operational efficiency.