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Travel time prediction in Austin, TX using the dataset provided by the City of Austin.

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ATXHackTheTraffic

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This is a project for travel time prediction in Austin, TX using the dataset provided by the City of Austin.

Quick Overview

Make sure you have Python 2.7 installed on your system.

Install Dependencies

pip install -r requirements.txt

Database Setup

  1. Download Bluetooth Travel Sensor data from City of Austin Website
  2. Put Travel_Sensors.csv and Bluetooth_Travel_Sensors_-Traffic_Match_Summary_Records__TMSR_.csv in the project folder.
cd database_processing
python preprocess.py

Start Server

python run.py

Open http://localhost:8000/ to see the app running.

Features

Travel Time Prediction

Select the origin, destination and time to see how long it takes to get there. Image of travelTimePrediction

History Stats

See the history stats for the average travelling time between each station. Image of historyStats

Traffic Heat Map

Overview the traffic on Lamar Road based on different section and time. Image of trafficHeatMap

Technical Details

Server Routes

They are stored inside views folder. To add a new route,

  1. Add a new .py file in views/
  2. Import it into run.py
  3. Register the blueprint to our app.

The new .py file should have a format like this:

from flask import Blueprint

routeName = Blueprint('routeName', __name__)

@routeName.route("/routeName", methods=['GET'])
def routeName_function():
    return "The new route page."

Tests

Tests are put in tests folder. If you want to import something from the top level module, add it to context.py and then import to your test file.

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Travel time prediction in Austin, TX using the dataset provided by the City of Austin.

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