Anup Kumar,
Abushahama Khan,
Jakaryia Khan,
Sakshi Rastogi,
- , Student, Department of Computer Science- Artificial Intelligence and Machine Learning, Bansal Institute of Engineering and Technology, India, ,
- , Student, Department of Computer Science- Artificial Intelligence and Machine Learning, Bansal Institute of Engineering and Technology, India, ,
- , Student, Department of Computer Science- Artificial Intelligence and Machine Learning, Bansal Institute of Engineering and Technology, India, ,
- , Student, Department of Computer Science- Artificial Intelligence and Machine Learning, Bansal Institute of Engineering and Technology, India, ,
Abstract
An artificial intelligence (AI)-based traffic management system is an innovative and intelligent project for improving urban traffic control and emergency response using AI and artificial vision. With the rapid increase in vehicle numbers and urban populations, traditional traffic management systems are unable to effectively address all real-time traffic situations due to congestion, fuel consumption, and emergency deceleration. To address these limitations, this project utilizes the YOLOv8 (You Only Look Once, version 8) deep learning model for training and classification in real time. The continuous analysis system streams video directly from a traffic camera for vehicle density monitoring, identification, and first aid in emergency situations, as well as for ambulances and emergency services, and for dynamic optimization over several hours. Integrated Python, OpenCV, and Ultralytics YOLOv8 systems utilize Flask or Django web technologies for development and server-side visualization. When you receive an emergency alert, the AI model prioritizes your route to ensure fast and safe passage. The system provides access to statistical data and analytics from all authorities, enabling data-driven decision-making and continuous improvement. This core AI solution not only improves safety but also reduces time and effort, minimizes fuel consumption, and reduces carbon dioxide emissions. It guarantees efficient road traffic management and supports modern rapid response mechanisms in all emergency situations. The project represents an important vision for creating a smart city through technology and intelligent collaboration to create more efficient, faster, and more reliable transportation systems. Adapting this system to various geographic regions allows for its implementation, providing a scalable, cost-effective, and futuristic solution, as well as addressing the most pressing needs of modern urban life: traffic congestion and emergency prioritization.
Keywords: Artificial intelligence (AI), intelligent traffic management, YOLOv8, computer vision, emergency vehicle priority, traffic density monitoring, smart city, real-time vehicle detection, traffic optimization, carbon emission reduction
[This article belongs to Trends in Transport Engineering and Applications ]
References
An artificial intelligence (AI)-based traffic management system is an innovative and intelligent project for improving urban traffic control and emergency response using AI and artificial vision
Trends in Transport Engineering and Applications
| Volume | 13 | |
| Issue | 02 | |
| Received | 20/07/2026 | |
| Accepted | 23/07/2026 | |
| Published | 30/07/2026 | |
| Publication Time | 10 Days |