Traffic Automation

 Status : Completed

Tags: python Deep Learning



AIM

To train a deep learning model from vehicle detection and classification for automating traffic flow.


COMPONENTS AND TECHNOLOGIES USED

  • Deep Learning

  • Image Processing

  • Tensorflow

  • Google Colab


OVERVIEW

The main purpose of our project  is to train a vehicle detection model and apply it to create an algorithm for smooth flow of traffic. The model not only detects the vehicles but also classifies it into categories to define the density of each vehicle type.

Our algorithm for traffic automation is based on clearing the traffic according to the calculated total density of each lane and providing each lane the required time for the flow of traffic.

Project By: 

  1. Vivek Rai (20185024)
  2. Alok Kumar Singh (20195062)
  3. Saurabh Kumar Kaushal (20194044)

Mentored By: Gaurav Bansal (20165142)

Future applications:

  1. Model can be further improved to identify accidents on roads to call for immediate help.
  2. Model can be modified to clear roads immediately for emergency vehicles like ambulances, fire brigade etc.