A Particle Swarm Optimisation with Linearly Decreasing Weight for Real-Time Traffic Signal Control - Yanjun Shi (MDPI AG, 2021)
Nowadays, traffic congestion has become a significant challenge in urban areas and densely populated cities. Real-time traffic signal control is an effective method to reduce traffic jams. This paper proposes a particle swarm optimisation with linearly decreasing weight (LDW-PSO) to tackle the signal intersection control problem, where a finite-interval model and an objective function are built to minimise spoilage time. The performance was evaluated in real-time simulation imitating a crowded intersection in Dalian city (in China) via the SUMO traffic simulator. The simulation results showed that the LDW-PSO outperformed the classical algorithms in this research, where queue length can be reduced by up to 20.4% and average waiting time can be reduced by up to 17.9%.