IoT based Traffic Signals, developed to be implemented in special conditions to manipulate the Traffic Lights during a Green Coridor
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Updated
Nov 25, 2022 - C++
IoT based Traffic Signals, developed to be implemented in special conditions to manipulate the Traffic Lights during a Green Coridor
Traffic Signal Controll by Tracking, counting and speed estimation of vehicles on surveillance cameras using YOLO v9 and Reinforcement Learning
Algorithm for distributed traffic signal control
Scalable Reinforcement Learning Framework for Traffic Signal Control under Communication Delays
Code for "Traffic Signal Cycle Control with Centralized Critic and Decentralized Actors under Varying Intervention Frequencies"
🚦 Smart Traffic Signal System with Vehicle Detection using Arduino! 🚗 Optimizes traffic flow with dynamic signal adjustments. Two Arduino UNO boards orchestrate the magic. Simulated on Tinkercad for easy testing. 🌐
This project is a part of my Master's thesis and aims to improve traffic flow and reduce delays with the power of AI.
Study on the application of reinforcement learning to the management of a traffic light intersection.
The arduino code for the desity based traffic signal system
The provided Blazor code implements a Traffic Signal Management system featuring two sections: the Traffic Analyzer and Global Configuration. The Traffic Analyzer displays real-time traffic information, including current and next open directions, remaining time, and selected direction, with dynamically changing button colors indicating intervals.
Adaptive traffic signal control using deep reinforcement learning built using SUMO
Investigating Q-Learning and DQN variants for Traffic Signal Control problem
Designing and Modelling of an Intelligent Traffic Signal Controller using FSM in Verilog HDL
Integrate AutoRL into DQN to implement a single traffic signal control system.
This repository contains the code for the paper "LLM-Assisted Light: Leveraging Large Language Model Capabilities for Human-Mimetic Traffic Signal Control in Complex Urban Environments".
The "Traffic Congestion Reduction with SARSA" applies SARSA reinforcement learning for efficient urban traffic and pedestrian management, incorporating simulation, algorithmic implementation, and evaluation to enhance safety and reduce congestion.
SUMO Pytorch Deep Reinforcement Learning Traffic Signal Control
Investigating Q-Learning and DQN variants for Traffic Signal Control problem
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