Intelligent traffic congestion system design / Muhammad Arif Isham, Puteri Sarah Mohamad Saad and Yusnira Husaini - Isham, Muhammad Arif; Mohamad Saad, Puteri Sarah; Husaini, Yusnira (2022)
Road congestion has been an issue in big cities, especially during peak hours. Traffic congestion occurs when overflowing cars on the roads and lanes resulting in slower speeds, longer travel times and increased delays for drivers. A few key factors leading to traffic congestion, specifically in Kuala Lumpur, are inefficient traffic control, vehicle accidents, insufficient parking space, and road work. A non-effective traffic light system will create worse traffic congestion during peak hours in the city (Abdelfatah et al., 2015). Hence, a newly designed solution is developed to solve those problems. In this project, the focus is on user-centric traffic management by improving inefficient control of traffic. The aim is to improve the traffic light system in the city so that users can have a pleasant traffic experience. The theory is to install sensors near the lane to provide inputs to the smart traffic light. Artificial intelligence (AI) vehicle detection in traffic lights decides a reasonable duration of green light for congested lanes. Another innovative feature in the system is the Kuala Lumpur Intelligent Congestion (KLIC) System application that integrates traffic monitoring and short messages notification system. All these three features, KLIC apps, camera live feed video, and notification system, have been developed as proof of concept. The current traffic light system can drastically improve the city's road congestion because users can start planning their journey before leaving their home after viewing live feed video of the traffic.