ADDMS: Advanced Driver Digital Monitoring System for Efficient Intelligent Traffic Management

Safety and security of passengers, drivers, and pedestrians is very important for any Intelligent Traffic Management System (ITMS). Security and safety can be provided in terms of protection from ill-legal activism, collision with other vehicles, extended part of the vehicle or any other stationery or moving object. To avoid accidents, the accurate positions of other vehicles or objects along with its own positions on the road should be known. The position on the road can be identified using lane detection. YOLO, a convolutional neural network-based Accident-avoidance method is proposed in this article. The proposed method keeps track of the surrounding vehicles and objects by providing live video to the YOLO model. If any vehicle or objects are obstructing its path them the model will check the safety distance to switch the lane if possible. The vehicle will switch lanes if it is safe to switch the lane, i.e., if the neighboring is free then switch the lane otherwise slow down the speed to avoid the accident. The results show that the proposed model provides accurate results.