ATLAS (Adaptive Traffic Light Automation System) is an AI-based traffic solution designed to enhance urban mobility by replacing fixed-timer signals with intelligent, real-time traffic control. Utilizing live camera feeds and YOLO-based deep learning models, this innovative system detects and classifies vehicles, analyzes lane-wise congestion, identifies lane changes, and prioritizes emergency vehicles to dynamically adjust traffic light timings. Additionally, a secondary color-based computer vision method serves as a lightweight fallback for low-resource environments. By allocating green lights based on actual demand, ATLAS significantly reduces waiting times, improves traffic flow, and provides a scalable, smart-city–ready approach to modern urban mobility.
TL;DR: Develop an adaptive traffic light automation system powered by AI that adjusts in real-time to traffic conditions, prioritizes emergencies, and reduces waiting time through AI-based traffic solutions using computer vision and deep learning.