A Study of Sam Yan Intersection Traffic Signal Management Optimization

Abstract

Traffic lights are essential tools for controlling the flow of traffic at intersections, ensuring smooth and safe movement of vehicles and pedestrians. Nowadays, the traffic volume in cities has significantly increased, resulting in traffic congestion. This congestion causes unnecessary energy waste, air pollution that harms public health, and various social and economic problems. It is crucial to find solutions to traffic congestion for the betterment of the environment and the well-being of city residents. Developing more effective signal timing will result in positive changes in traffic flows and is key to addressing traffic congestion problems. This research project aims to study traffic characteristics and the relationship between traffic signals and traffic flows. Data was collected through field traffic observations over a period of several months and analyzed using Anylogic modeling software, which simulates various traffic scenarios. The study found that altering the green light duration affects overall traffic flow and delay. For instance, optimizing the green light duration based on real-time traffic conditions significantly improved traffic flow and reduced delays at intersections. However, the optimal duration may vary depending on factors such as time of day, traffic volume, and intersection design. The results of this study can be useful for temporary or permanent improvement of traffic signals at intersections and can also serve as valuable information for traffic officers in the area. Future research could explore the impact of other traffic management strategies, such as adaptive signal control technologies and traffic demand management techniques, to further alleviate traffic congestion in cities.