Author:
Dr. Sheshang Degadwala ,Ravindra Baria
Abstract
The differential analysis of emergency vehicle detection in urban traffic is crucial for improving response times and reducing traffic-related delays during emergencies. This systematic review aims to analyze various methods and technologies, such as acoustic, visual, and sensor-based systems, used for detecting emergency vehicles in complex urban environments. The motivation behind this study is the growing need for more efficient traffic management systems that prioritize emergency vehicles, minimizing delays caused by congestion. However, limitations include the inconsistent performance of detection systems in varying weather, lighting, and noise conditions, as well as integration challenges with existing infrastructure. The objective is to evaluate current detection methods, identify their limitations, and propose potential improvements to enhance the accuracy and reliability of emergency vehicle detection in urban traffic systems.
Reference58 articles.
1. Zohaib, Muhammad, et al. “Enhancing Emergency Vehicle Detection: A Deep Learning Approach with Multimodal Fusion.” Mathematics, vol. 12, no. 10, 2024, pp. 1–23, https://doi.org/10.3390/math12101514.
2. Malse, Prashant Nivrutirao, et al. “Traffic Signboard And Ambulance Detection System.” COMPUTER RESEARCH AND DEVELOPMENT, vol. 24, no. 1000, 2024, pp. 16–19.
3. Salem Jeyaseelan, W. R., et al. “Efficient Intelligent Smart Ambulance Transportation System Using Internet of Things.” Tehnicki Vjesnik, vol. 31, no. 1, 2024, pp. 171–77, https://doi.org/10.17559/TV-20230726000829.
4. Shatnawi, Mo’ath, and Maram Bani Younes. “An Enhanced Model for Detecting and Classifying Emergency Vehicles Using a Generative Adversarial Network (GAN).” Vehicles, vol. 6, no. 3, 2024, pp. 1114–39, https://doi.org/10.3390/vehicles6030053.
5. Amrutasagar, K., et al. “Enhanced Traffic Signal Adaptation with Ambulance Identification and Distance Computation.” International Journal of Computing and Digital Systems, vol. 10, no. 1, 2024, pp. 1–10, https://journal.uob.edu.bh/handle/123456789/5527.