A Smart AI Based Solution Traffic Management with Real-Time Monitoring and Adaptation of Traffic Light Timings

• Author(s): Samiksha Debe; Tanmay Patil; Saniya Gawande; Shivam Panzade; Prajwal Patil
• Paper ID: 1712839
• Page: 2106-2113
• Published Date: 29-12-2025
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 9 Issue 6 December-2025

Abstract

Traffic congestion in urban areas has become a critical challenge due to the increasing number of vehicles and inefficient signal management. Traditional traffic control systems lack adaptability, leading to delays and higher fuel consumption. This paper explores AI-driven traffic management using deep learning models like YOLOv8 for real-time vehicle detection and adaptive signal control. By integrating computer vision and machine learning, these systems optimize traffic flow, improve emergency response, and reduce environmental impact. While AI-based solutions offer significant advantages, challenges such as implementation complexity and scalability persist. This review highlights key advancements and future directions in intelligent traffic management.

Keywords

Smart Traffic Management, Artificial Intelligence (AI), YOLO Object Detection, Deep Learning, Reinforcement Learning

Citations

IRE Journals:
Samiksha Debe, Tanmay Patil, Saniya Gawande, Shivam Panzade, Prajwal Patil "A Smart AI Based Solution Traffic Management with Real-Time Monitoring and Adaptation of Traffic Light Timings" Iconic Research And Engineering Journals Volume 9 Issue 6 2025 Page 2106-2113 https://doi.org/10.64388/IREV9I6-1712839

IEEE:
Samiksha Debe, Tanmay Patil, Saniya Gawande, Shivam Panzade, Prajwal Patil "A Smart AI Based Solution Traffic Management with Real-Time Monitoring and Adaptation of Traffic Light Timings" Iconic Research And Engineering Journals, 9(6) https://doi.org/10.64388/IREV9I6-1712839