This study addresses the traffic signal optimization problem at a median-west median intersection. Based on 36 days of time-segmented traffic volume data, it combines the NS traffic flow model, Webster signal timing model, and genetic algorithm to propose a dynamic phase control scheme. By analyzing the traffic characteristics during morning rush hour, evening rush hour, off-peak hours, and nighttime, differentiated signal phases are designed: high-flow turning maneuvers (such as U-turns and left turns) are prioritized during peak hours, combined phases are added during off-peak hours, and induction control is used at night. After optimization, the average speed on the main road during morning rush hour increases from 28 km/h to 42 km/h, with delays reduced by 35%, and off-peak traffic capacity improves by 25%. The scheme achieves maximum traffic flow speed on the main road through phase conflict avoidance, green wave coordination, and dynamic parameter adjustments, providing a data-driven and model-coordinated solution for optimizing complex urban intersections.

Nan Cao, Xueyan Hu, Xinyi Gao. Study on Traffic Flow Control Based on Matlab Data Analysis. Academic Journal of Engineering and Technology Science (2025), Vol. 8, Issue 4: 102-109. https://doi.org/10.25236/AJETS.2025.080414.

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