ENHANCING TRAFFIC CONTROL EFFICIENCY IN BENIN CITY USING REALTIME MONITORING, MACHINE VISION AND TIMING OPTIMIZATION TECHNIQUES

ABSTRACT

This project aims to design and implement an intelligent traffic light control system that addresses the complexities of urban mobility, aiming to enhance efficiency and reduce congestion. The motivation behind this work stems from the ever-growing challenges posed by urbanisation, where traditional traffic management systems often fall short in adapting to dynamic traffic patterns. By developing a smart traffic light control system, we intend to optimise signal timings based on real-time traffic data, thereby improving the overall flow of vehicles and minimising delays. In implementing this project, the methodology will involve the integration of advanced sensor technologies, machine learning algorithms, and communication networks. Sensors will be placed at intersections to collect traffic data, such as vehicle density and flow rates. Machine learning models will then analyse this information to predict traffic patterns, which will enable the system to adjust signal timings dynamically. Furthermore, communication networks will facilitate coordination between intersections, allowing for synchronised traffic light adjustments to optimise traffic flow. The expected result of this project is a sophisticated traffic light control system that significantly enhances urban mobility. By intelligently adapting to changing traffic conditions, the system aims to reduce travel times, fuel consumption, and environmental impact. The anticipated outcome is a tangible improvement in overall traffic efficiency and a more sustainable urban transportation infrastructure. This project lays the foundation for 11 smarter, ui adaptive traffic management systems, contributing to the advancement of intelligent urban mobility solutions