Advancing Urban Transportation Management: A Comprehensive Review of Computer Vision-Based Vehicle Detection and Counting Systems

Manish Mathur, Mrinal Kanti Sarkar, G. Uma Devi

2024

Abstract

In the landscape of urban transportation management, computer vision-based vehicle detection and counting systems have emerged as transformative solutions. This review delves into the evolution and efficacy of such systems in modern traffic control. Examining a spectrum of methodologies, from traditional to deep learning approaches, the study highlights how computer vision accurately tracks and tallies vehicles on roads and highways. These systems provide real-time insights, aiding authorities in identifying congestion points, optimizing signal timings, and implementing dynamic lane management strategies. Moreover, they facilitate diverse applications like toll collection and parking management, enhancing overall transportation efficiency and safety. With their adaptability across environments and seamless integration into existing infrastructure, these systems are indispensable for modern transportation authorities. This review emphasizes their role in advancing urban transportation management, promising tangible enhancements in traffic flow efficiency, safety, and urban mobility.

Paper Citation

in Harvard Style

Mathur M., Sarkar M. and Devi G. (2024). Advancing Urban Transportation Management: A Comprehensive Review of Computer Vision-Based Vehicle Detection and Counting Systems. In Proceedings of the 1st International Conference on Cognitive & Cloud Computing - Volume 1: IC3Com; ISBN 978-989-758-739-9, SciTePress, pages 196-204. DOI: 10.5220/0013305600004646

in Bibtex Style

@conference{ic3com24,
author={Manish Mathur and Mrinal Kanti Sarkar and G. Uma Devi},
title={Advancing Urban Transportation Management: A Comprehensive Review of Computer Vision-Based Vehicle Detection and Counting Systems},
booktitle={Proceedings of the 1st International Conference on Cognitive & Cloud Computing - Volume 1: IC3Com},
year={2024},
pages={196-204},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013305600004646},
isbn={978-989-758-739-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Cognitive & Cloud Computing - Volume 1: IC3Com
TI - Advancing Urban Transportation Management: A Comprehensive Review of Computer Vision-Based Vehicle Detection and Counting Systems
SN - 978-989-758-739-9
AU - Mathur M.
AU - Sarkar M.
AU - Devi G.
PY - 2024
SP - 196
EP - 204
DO - 10.5220/0013305600004646
PB - SciTePress