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May 2, 2026Open Access

Ai-Driven Adaptive Traffic Signal Control System

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Authors

PAPranavvikraman. ADSDr. M. Sakthivanitha

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Overview

Randomized trial demonstrates reduced delays and improved throughput in urban traffic management.

Key Points

  • The aim is to develop an AI-driven system that adapts traffic signals in real time to reduce congestion and improve safety at intersections.
  • Implemented an AI-based control system at a six-road intersection in Chennai.
  • Utilized Python backend, OpenAI's GPT-5.4-nano model, Flask, and Socket.IO for real-time signal adjustments.
  • Monitored vehicle counts across nine lane paths to adjust signal timings for five units.
  • Reduced delays in vehicle movement during peak hours, resulting in enhanced throughput.
  • Improved pedestrian safety with better signal timing.
  • Demonstrated economic viability with operational costs of USD 0.20 per million tokens.

Cite This Study

A et al. (2026) studied this question.

synapsesocial.com/papers/69f5955971405d493a0003a2https://doi.org/10.5281/zenodo.19911257
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