MUMBAI, India, Oct. 5 -- Intellectual Property India has published a patent application (202641115738 A) filed by Nidhi Singh M; Dr. Mamatha C M; Priya R Ganiger; Vannalu Ashritha; Nikita Dangi; Yukthi Subramani; Somanath; Supriya P; and Cambridge Institute Of Technology North Campus on September 26, 2026, for Ai-Based Reservation Smart Traffic System.
Inventors include Nidhi Singh M; Dr. Mamatha C M; Priya R Ganiger; Vannalu Ashritha; Nikita Dangi; Yukthi Subramani; Somanath; Supriya P; and Cambridge Institute Of Technology North Campus.
The application for the patent was published on October 02, 2026, under issue no. 40/2026.
Abstract: The proposed AI-Based Reservation Smart Traffic System is an intelligent traffic management framework designed to reduce traffic congestion, vehicle waiting time, fuel consumption, emissions, and inefficient utilization of road intersections. The system integrates Artificial Intelligence, Machine Learning, IoT, GPS, traffic sensors, cameras, Vehicle-to-Infrastructure (V2I) communication, predictive analytics, and intelligent scheduling. The system uses a reservation-based mechanism in which approaching vehicles transmit information including location, lane, speed, acceleration, estimated arrival time, intended movement, and priority level. The AI-based traffic management server analyzes this information together with real-time traffic data to predict vehicle arrival times, identify potential conflicts, and assign suitable crossing time slots. The reservation schedule is continuously updated according to changing traffic conditions, vehicle movements, and newly arriving vehicles. Emergency vehicles such as ambulances, fire trucks, and police vehicles may receive priority crossing opportunities through dynamic modification of existing reservations. The generated traffic instructions are communicated to connected vehicles and roadside infrastructure through V2I communication. Smart traffic signals, vehicle displays, navigation systems, and roadside displays can execute or communicate the instructions. The system also monitors waiting time, throughput, queue length, travel time, fuel consumption, emissions, vehicle stops, and emergency response time. The proposed framework provides dynamic and adaptive intersection management, with the objective of reducing unnecessary stopping and waiting, improving traffic flow, supporting emergency response, reducing fuel consumption and emissions, and supporting intelligent transportation infrastructure.
Disclaimer: Curated by HT Syndication.
