🚗 A repository for documenting and exploring the world of autonomous driving safety, featuring a curated collection of research papers, reports, and resource.

ASTMS : Autonomous Smart Traffic Management System Leveraging Artificial Intelligence CNN and Long Short Term Memory

Smart Traffic Solutions for Traffic Congestion and Emissions Reduction Paper ♻️

Adaptive traffic signal management with YOLOv8 + SORT: real‑time vehicle counting, line crossing, and congestion‑aware timing

Reinforcement Learning based adaptive traffic signal control system using Python, Pygame, PyTorch and Stable-Baselines3.

Comparison between Artificial Intelligence handled traffic lights and manual or cycle based changing lights.

This project is a Streamlit web application designed to analyze traffic violation data. It provides a user-friendly interface to explore, visualize, and gain insights from traffic violation datasets. Users can upload their own data, perform analysis, and view summaries and trends.

Hybrid LSTM + Meta-Heuristic Traffic Signal Optimization — Blida, Algeria

IoT laboratory project implementing an automated traffic light system using Arduino UNO, ESP-01 (ESP8266), and ThingSpeak, enabling real-time monitoring and remote control of traffic signal states via cloud communication (Internet of Things, UNIWA).

This project uses reinforcement learning to optimize traffic signals, reducing congestion and improving flow through dynamic adjustments and simulation analysis.

ML-based smart traffic control system using AWS (S3, Lambda, IoT) with real-time inference and hybrid decision logic

Smart traffic management dashboard using IoT sensors and Cumulocity to monitor intersections, signals, and traffic conditions.

STSP Reference Implementation — Smart Traffic Synchronization Protocol (draft-aldana-stsp-00 · IETF)

AI Smart Traffic System - AI & IoT Integration project in AI / ML / GenAI for CSEProjects360 final year project catalog.

A Spring Boot microservice dedicated to managing real-time traffic signal states and control logic within the Traflux AI ecosystem.

Smart traffic signal controller designed using Verilog HDL, based on Finite State Machine (FSM) logic. The project focuses on simulation-based verification using testbenches and waveform analysis with GTKWave, demonstrating core FPGA and digital design concepts.

🚦 Smart traffic light system using YOLO11 real-time vehicle detection, ESP32 control, HC-SR04 ultrasonic sensor, and a live web dashboard — built for intelligent intersection management.

An IoT-enabled traffic management system designed to prioritize ambulance movement at intersections. The system uses real-time location data and a priority-based algorithm to dynamically control traffic signals, reducing emergency response time and improving road safety.

Scalable Smart Traffic Data Analytics with Anomaly Detection using Apache Spark (Databricks)

AI-powered junction optimization system for adaptive traffic control, emergency vehicle prioritization, congestion prediction, and intelligent traffic flow management.