AI Powered Traffic Signal Control System Using Reinforcement Learning

S. Saritha, Challa Sree Lakshmi, Gumpu Keerthana, Boda Uma Jyothsna, Adimulam Sree Lakshmi

2025

Abstract

Designed to maximise urban mobility via real-time data inputs, the AI-Powered Traffic Signal Control system is a smart traffic management tool. The user interface, as depicted in the screenshot, is a form where critical traffic parameters such as intersection ID, number of cars, average speed, emergency vehicle detection, and pedestrian count are entered. By use of dynamic traffic condition analysis, these inputs enable the system to make adaptive signal changes to enhance traffic flow and lower congestion. It employed machine learning and artificial intelligence to analyse the real-time traffic data in shorter time. Emergency vehicle identification displayed as a read-only field in the interface may indicate a form of automation whereby artificial intelligence recognizes and prioritizes emergency vehicles for uninterrupted passage. Pedestrian count integration ensures crosswalk timing is optimised for safety and efficiency. Depending on these inputs, the system dynamically modifies traffic signals to maximise general traffic throughput and minimise wait times. AI-Powered Traffic Signal Control solution is very useful especially with smart city projects where data-driven decisions help optimize an urban infrastructure. The technology contributes to environmental sustainability, reduces fuel consumption, and removes unnecessary stops. A simple and accessible but powerful interface enables city planners and traffic controllers to easily monitor and manage traffic conditions, helping to ensure safer and more fluid movement for all road users.

Paper Citation

in Harvard Style

Saritha S., Lakshmi C., Keerthana G., Jyothsna B. and Lakshmi A. (2025). AI Powered Traffic Signal Control System Using Reinforcement Learning. In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25; ISBN 978-989-758-777-1, SciTePress, pages 364-369. DOI: 10.5220/0013898200004919

in Bibtex Style

@conference{icrdicct`2525,
author={S. Saritha and Challa Lakshmi and Gumpu Keerthana and Boda Jyothsna and Adimulam Lakshmi},
title={AI Powered Traffic Signal Control System Using Reinforcement Learning},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25},
year={2025},
pages={364-369},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013898200004919},
isbn={978-989-758-777-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25
TI - AI Powered Traffic Signal Control System Using Reinforcement Learning
SN - 978-989-758-777-1
AU - Saritha S.
AU - Lakshmi C.
AU - Keerthana G.
AU - Jyothsna B.
AU - Lakshmi A.
PY - 2025
SP - 364
EP - 369
DO - 10.5220/0013898200004919
PB - SciTePress