Advance Traffic Management System (ATMS) using AI

• Author(s): Kunal Paswan; Seemit Kumar; Mukul Chuadhary; Vikash Rana
• Paper ID: 1712789
• Page: 1798-1800
• Published Date: 24-12-2025
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 9 Issue 6 December-2025

Abstract

Urban traffic jams have become one of the biggest headaches of contemporary cities. Fixed traffic lights do not adjust to dynamic changes, causing greater jams, fuel loss, and air pollution. This project suggests an Advanced Traffic Management System (ATMS) based on rule-based Artificial Intelligence. The system will dynamically adjust traffic lights based on real-time traffic density input captured through sensors or simulated networks. In contrast to conventional systems, ATMS will also grant priority passage to emergency vehicles and live monitoring through a dashboard. The solution is scalable, low-cost, and can be extended in the future with IoT and ML integration.

Keywords

Traffic Management, Artificial Intelligence, Traffic Flow Control, Rule Based AI, Reinforcement Learning

Citations

IRE Journals:
Kunal Paswan, Seemit Kumar, Mukul Chuadhary, Vikash Rana "Advance Traffic Management System (ATMS) using AI" Iconic Research And Engineering Journals Volume 9 Issue 6 2025 Page 1798-1800 https://doi.org/10.64388/IREV9I6-1712789

IEEE:
Kunal Paswan, Seemit Kumar, Mukul Chuadhary, Vikash Rana "Advance Traffic Management System (ATMS) using AI" Iconic Research And Engineering Journals, 9(6) https://doi.org/10.64388/IREV9I6-1712789