A STUDY ON OPTIMIZING TRAFFIC SIGNAL CONTROL FOR IMPROVED TRAFFIC FLOW

Abstract

Addressing traffic congestion holds paramount importance due to its severe economic and environmental repercussions. This study introduces an approach to address this pervasive issue by employing a wide-area control strategy for diverse road networks. The strategy leverages a dynamic offset control method and a multi-agent model to create a unique solution. In this framework, individual intersections function as distinct agents, engaging in negotiations, establishing connections, and forming a dynamic offset control zone resembling a tree structure. Within this structure, agents collaboratively manage green wave synchronization based on real-time traffic conditions at the network boundaries. To evaluate the effectiveness of this approach, comprehensive tests utilize both a simulated road network (Experiment 1) and an actual grid-like road network (Experiment 2). In Experiment 1, the proposed method consistently reduces lost time, resulting in an average reduction of 15% across all scenarios. Experiment 2 demonstrates a reduction in lost time across various intervals, with an impressive average reduction of 34% in lost time across all scenarios. These results demonstrate the strategy's ability to dynamically and adaptively establish green waves that significantly enhance traffic flow. In conclusion, this study demonstrates that the proposed method autonomously conducts offset control, effectively contributing to the smooth flow of vehicles.