One of the biggest issues in metropolitan areas is traffic congestion, despite having well-planned road systems and adequate infrastructure. The main cause of this issue is the 40% annual increase in the number of cars on the road. Most current traffic control systems are fixed cycle types, which always cycle through red, yellow, and green. The deployment of these pilots is accompanied by the deployment of traffic police officers to maintain order in the streets. Unlike human traffic cops, these inflexible systems cannot adjust to changing circumstances on the fly. Intelligent traffic management systems are needed immediately. In order to measure traffic volume, our proposed system will use AI and image processing to analyse live feeds from cameras placed at intersections. The amount of vehicles passing through the intersection is predicted to increase by around 32% based on simulation results, which is a substantial gain over the status quo. More training and calibration of the model with actual CCTV data can bring about significant improvements in the system's performance. 

Sergey Shklyaev

Papers

Smart Traffic Signal Control System Using Artificial Intelligence