Intelligent Traffic Management System Based on AI and IoT

Abstract

The high number of vehicles on the roads today poses a serious hurdle with respect to traffic management on the roads, particularly considering the worsening and narrowed state of Tiaret’s road infrastructure. Inflexible traffic signal scheduling at every intersection complicates traffic congestion, environmental deterioration, excessive fuel usage, and driver dissatisfaction. The proposed solution for this problem includes an artificial intelligence and Internet of Things-based system that operates on the premise of real-time processing of data. Traffic congestion within metropolitan areas is a chronic problem that results in traffic bottlenecks, environmental deterioration, and issues of ensuring road safety. This study assumes the implementation and development of a holistic traffic management system based on Artificial Intelligence and the Internet of Things to streamline traffic movement and enhance road safety. Under the suggested framework, the detection and enumeration of vehicles and pedestrians are achieved using real-time video input along with object identification techniques. The observations are then analyzed to control traffic signal duration according to usage levels of roads, pedestrian requirements, and emergency vehicle prioritization. The Raspberry Pi 5 is used as the computational unit to implement this framework practically. It is expected to enhance traffic functioning efficiency and response times while being a cost-effective and efficient solution to deploy within smart city projects