R-INTEGRATE- AN INTEGRATED AI-DRIVEN INTELLIGENT ROAD MOBILITY AND TRAFFIC MANAGEMENT SYSTEM A proposed framework for real-time traffic and emergency management, road safety and user-oriented transportation
Ritesh Rangar · Aug 15, 2026
Author 1: Ritesh Rangar Author 2: Priyanka Singh Rajput Date: 15 August 2026 Abstract Traffic management in cities is becoming increasingly difficult because of the growing number of vehicles, congestion, accidents, road construction, poor road conditions and delays faced by emergency vehicles. Many technologies are already being used to deal with these problems, including traffic cameras, sensors, automated traffic enforcement, navigation systems and adaptive traffic signals. However, these technologies are often developed and operated for individual purposes. This paper proposes an integrated AI-driven road mobility system in which cameras, sensors, connected traffic signals and other data sources communicate with each other using IoT and a main central server. The server analyzes information collected from the road and takes appropriate actions according to the situation. For example, if an ambulance or fire vehicle is detected approaching an intersection, the system can identify its direction and provide appropriate signal priority. If one side of an intersection has a much larger vehicle queue, signal timing can be adjusted to improve traffic flow. Accidents, potholes, road construction and other road conditions can also be detected and reported. A connected website would act as the user-facing part of the system. It could display traffic conditions, congestion zones, construction information and traffic-signal status, while providing route options based on factors such as distance, congestion, expected signal delay and road condition. Instead of forcing every user to choose the same type of route, the system would allow users to decide what matters most to them, such as minimum distance, minimum travel time or better road conditions. Its main contribution is the integration of road detection, traffic management, emergency response, road maintenance and user information into one coordinated framework. The study also discusses the challenges of data accuracy, privacy, infrastructure requirements and the need for human or authorized verification in safety-critical and enforcement-related actions.