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Traffic Simulation

This is a GitHub repository for a traffic simulation project. The project aims to simulate and analyze traffic patterns using a customizable simulation environment.

Table of Contents

Introduction

The Traffic Simulation project provides a platform to simulate and study various aspects of traffic behavior. It allows users to create custom scenarios, modify parameters, and observe how different factors affect traffic flow, congestion, and other related metrics.

Features

  • Scenario Creation: Users can create custom traffic scenarios by defining road networks, intersections, traffic signals, and vehicle types.

  • Realistic Simulation: The simulation engine provides a realistic representation of traffic behavior, taking into account factors such as vehicle acceleration, deceleration, lane changing, and interaction with traffic signals.

  • Visualization: The simulation results are visualized using interactive graphs and maps, enabling users to analyze traffic patterns, congestion levels, and other metrics.

  • Metrics and Analysis: The project includes built-in tools to measure and analyze various traffic-related metrics, including traffic flow, average speed, travel time, and vehicle density.

Installation

To use this project, follow these steps:

  1. Clone the repository:
git clone https://github.com/GarettPF/Traffic-Simulation.git
  1. Navigate to the project directory:
cd Traffic-Simulation
  1. Install the required dependencies:
pip install -r requirements.txt
  1. Run the simulation:
python simulation.py

Usage

Once the simulation is running, you can interact with it using the command-line interface or the provided graphical user interface (GUI). The GUI allows you to create scenarios, modify parameters, and observe the simulation results in real-time.

To create a new scenario, follow these steps:

  1. Launch the simulation.

  2. Use the GUI or the command-line interface to define the road network, intersections, traffic signals, and vehicle types.

  3. Start the simulation and observe the traffic behavior.

  4. Analyze the results using the provided visualization tools.

License

This project is licensed under the MIT License. See the LICENSE file for more information.

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  • Python 100.0%