Intelligent Traffic Management Systems: Case Studies and Real-World Applications
Year: 2025
Type: conference-paper
Abstract: This paper presents a real-time Intelligent Traffic Management System (ITMS) designed for urban smart cities with high congestion, limited human resources, and rising vehicle density. The system integrates AI/ML algorithms, OpenCV, OCR, and live Google Maps API to dynamically manage traffic signals, detect violations, and prioritize emergency routing through green corridors. The modular design includes components for license plate recognition, traffic statistics, fine automation, and a centralized operator dashboard. The proposed system was tested in simulation with over 98% license plate recognition accuracy and 95% violation detection accuracy. It demonstrates significant improvements in traffic flow, safety, and operational efficiency. This work is part of a broader vision for deploying scalable, smart, and adaptive traffic systems in India’s rapidly growing urban regions.
Author: Yadav, Nishant Kumar
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6912026039
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