Research Information System
2nd International Conference on Science, Engineering Management and Information Technology, SEMIT 2023, Ankara, Turkey, 14 - 15 September 2023, vol.2198 CCIS, pp.253-270, (Full Text)
The escalating challenges of urban traffic congestion, resulting in amplified time and economic losses, profoundly impact daily life. Inappropriate signal switching on ordinary roads is identified as a significant contributor to this issue. Traditional approaches relying on human experiences for manipulating parameters in general signal control often yield suboptimal outcomes. To address this critical problem, this research proposes a dynamic traffic signal control system using a multi-agent approach with the Deep Q-Network method. In this urgent scenario, the proposed system aims to achieve precise parameter manipulation within a road environment featuring multiple intersections. A meticulous comparative analysis is conducted against static signal control and non-coordinated multi-agent systems, incorporating detailed numerical results to assess performance metrics. Results from a comprehensive 500,000-step experiment reveal the proposed method’s adeptness in balancing performance and computational efficiency, leveraging inter-agent cooperation. “Comparison Method 3,” inspired by Joo and Lim’s methodology (2021), consistently outperforms others, particularly in congestion reduction.