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pds_traffic_management_system

This repository was created to showcase our work on a traffic system management for PDS college project at SPIT

https://github.com/yateen00/pds_traffic_management_system

Science Score: 31.0%

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    CITATION.cff file
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    .zenodo.json file
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    Low similarity (10.4%) to scientific vocabulary
Last synced: 10 months ago · JSON representation ·

Repository

This repository was created to showcase our work on a traffic system management for PDS college project at SPIT

Basic Info
  • Host: GitHub
  • Owner: Yateen00
  • License: mit
  • Language: Python
  • Default Branch: main
  • Size: 29.8 MB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created over 1 year ago · Last pushed over 1 year ago
Metadata Files
Readme License Citation

README.md

Traffic System Management at a Single Intersection Using PPO Reinforcement Learning

Project Overview

This project focuses on optimizing traffic flow at a single intersection using Proximal Policy Optimization (PPO) reinforcement learning. By training an AI model to manage signal timing dynamically, we aim to reduce vehicle wait times and improve overall traffic efficiency. This repository is a modified version of sumo-rl by LucasAlegre, customized to enhance its applicability to our objectives.
It also contains the YOLO prototype we plan to use for getting the observation space.

Team Members

All team members are students at Sardar Patel Institute of Technology.

Setup Instructions

Prerequisites

Ensure that Python is installed on your system. This setup was tested to work with Python 3.10.12.

YOLO Model Requirements

To use the YOLO model, download the following files and place them inside the YOLO folder:

Create Virtual Environments

  1. Set up a virtual environment for the YOLO folder:

bash cd YOLO python3 -m venv yolo-venv source yolo-venv/bin/activate

After activating the virtual environment, install the required packages:

bash pip install -r requirements.txt

To deactivate the virtual environment once you’re done:

bash deactivate

  1. Set up a virtual environment for the model folder:

bash cd ../model python3 -m venv model-venv source model-venv/bin/activate

Similarly, install the necessary dependencies:

bash pip install -r requirements.txt

To deactivate this virtual environment when finished:

bash deactivate

Switching Between Virtual Environments

  • When working with files in the YOLO folder, activate the yolo-venv:

bash cd YOLO source yolo-venv/bin/activate

  • When working with files in the model folder, activate the model-venv:

bash cd ../model source model-venv/bin/activate

Always ensure the correct virtual environment is active before running commands in each respective folder.

License

This project, and the project it's derived from i.e sumo-rl by LucasAlegre is released under the MIT License.

Owner

  • Login: Yateen00
  • Kind: user

Citation (CITATION.bib) 

@misc{AlegreSUMORL,
    author = {Lucas N. Alegre},
    title = {{SUMO-RL}},
    year = {2019},
    publisher = {GitHub},
    journal = {GitHub repository},
    howpublished = {\url{https://github.com/LucasAlegre/sumo-rl}},
}

GitHub Events

Total
  • Member event: 2
  • Push event: 11
  • Create event: 2
Last Year
  • Member event: 2
  • Push event: 11
  • Create event: 2

Dependencies

requirements.txt pypi
  • Farama-Notifications ==0.0.4
  • Jinja2 ==3.1.4
  • MarkupSafe ==3.0.2
  • cloudpickle ==3.1.0
  • contourpy ==1.3.0
  • cycler ==0.12.1
  • filelock ==3.16.1
  • fonttools ==4.54.1
  • fsspec ==2024.10.0
  • gymnasium ==0.29.1
  • kiwisolver ==1.4.7
  • matplotlib ==3.9.2
  • mpmath ==1.3.0
  • networkx ==3.4.2
  • numpy ==1.26.4
  • nvidia-cublas-cu12 ==12.4.5.8
  • nvidia-cuda-cupti-cu12 ==12.4.127
  • nvidia-cuda-nvrtc-cu12 ==12.4.127
  • nvidia-cuda-runtime-cu12 ==12.4.127
  • nvidia-cudnn-cu12 ==9.1.0.70
  • nvidia-cufft-cu12 ==11.2.1.3
  • nvidia-curand-cu12 ==10.3.5.147
  • nvidia-cusolver-cu12 ==11.6.1.9
  • nvidia-cusparse-cu12 ==12.3.1.170
  • nvidia-nccl-cu12 ==2.21.5
  • nvidia-nvjitlink-cu12 ==12.4.127
  • nvidia-nvtx-cu12 ==12.4.127
  • packaging ==24.2
  • pandas ==2.2.3
  • pettingzoo ==1.24.3
  • pillow ==11.0.0
  • pyparsing ==3.2.0
  • python-dateutil ==2.9.0.post0
  • pytz ==2024.2
  • seaborn ==0.13.2
  • six ==1.16.0
  • stable_baselines3 ==2.3.2
  • sumolib ==1.21.0
  • sympy ==1.13.1
  • torch ==2.5.1
  • traci ==1.21.0
  • triton ==3.1.0
  • typing_extensions ==4.12.2
  • tzdata ==2024.2