Signal control at urban arterial intersections based on genetic algorithm

In urban arterial intersections, unreasonable signal coordination can lead to a decrease in the efficiency of arterial traffic flow and an increase in vehicle start-stop frequencies. Phase difference is a crucial parameter for arterial signal coordination, as the phase difference between intersections affects the delay experienced by traffic flow. This paper focuses on the phase difference of consecutive intersections and proposes an optimization algorithm for arterial phase difference. It introduces a utility function based on the correlation analysis of multiple phase differences, utilizes neural networks to describe the relationship between phase difference and arterial delay, and employs genetic algorithms to find the optimal solution for the model. Simulation results demonstrate that the proposed arterial phase difference optimization algorithm outperforms traditional uncontrolled and induction-controlled methods, yielding superior signal control effectiveness.