Traffic Waves

Traffic-Waves is a voluntary project focused on daily traffic predictions in Paris, utilizing data from Open Data Paris

Overview

The project leverages ML and DL techniques to analyze historical traffic data and make predictions for daily traffic patterns in Paris. This aids in providing insights for commuters and city planners alike.

Pipeline components

The above command runs the following components:

Data:

• Data collection: Call the Open data Paris API and save the data in batches.
• Data processing: Merge the data and apply preprocessing steps to prepare data for batch predictions.

Machine learning:

• Model training: Import and train the ML model on the historical data.
• Predictions: Get the one-day ahead predictions using the trained model and batch data.

Visualization:

• Dashboard: Start a flask app to display the input data and predictions for all the links.

1. Download and Install

To install the requirements, run the following command in the parent:

git clone https://github.com/vishalmhjn/traffic-waves.git
cd traffic-waves
make install

Usage

Run the data collection, processing and machine learing pipeline (with default options):

make run

Run the visualization app:

make app

Visit http://127.0.0.1:5000/ in the web-browser to open the visualization dashboard.

2. Building and running your application using Docker

When you're ready with Docker installed, start your application by running: docker compose up --build.

Your application will be available at http://localhost:5000.

License

to be updated