This paper introduces a Smart Traffic Management System (STMS)employing RF sensors, cameras, and machine learning algorithms to monitor and optimize urban traffic. The system dynamically adjusts traffic signal timings, offers real-time route recommendations based on GPS data, and incorporates adaptive control mechanisms to reduce congestion and improve overall mobility. Simulation studies and real-world testing demonstrate the effectiveness of the STMS in enhancing traffic flow, minimizing waittimes, and contributing to sustainable urbandevelopment.
Smart Traffic Management System for Urban Mobility Enhancement Using RF Sensors, Cameras, and Machine Learning
2024-10-08
598068 byte
Conference paper
Electronic Resource
English
Urban Traffic Management using Machine Learning
IEEE | 2022
|Smart Traffic Light System Using Machine Learning
IEEE | 2018
|Traffic Management for Urban Air Mobility
British Library Conference Proceedings | 2019
|