Traffic Prediction for Intelligent Transportation System using Machine Learning

Project Code :TEMBMA3234

Objective

The main objective of this project is to Predict Traffic Density using Machine Learning for building Intelligent Transportation system

Abstract

The solution we provide for Traffic management by having a special intelligence which the images of road feed from the cameras (webcam or IP camera) at traffic junctions for real time traffic density calculation using image processing. It also focuses on the algorithm for switching the traffic lights according to vehicle density on the road, thereby aiming at reducing the traffic congestion on roads which will help lower the number of accidents. In turn, it will provide safe transit for people and reduce fuel consumption and waiting time. It will also provide significant data which will help in future road planning and analysis. In further stages multiple traffic lights can be synchronized with each other with an aim of even less traffic congestion and free flow of traffic. The vehicles are detected by the system through images instead of using electronic sensors embedded in the pavement. A camera will be placed alongside the traffic light. It will capture images sequences. Image processing is a better technique to control the state change of the traffic light. It shows that it can decrease the traffic congestion and avoids the time being wasted by a green light on an empty road. It is also more reliable in estimating vehicle presence because it uses actual traffic images.

Keywords: Raspberry Pi, Camera, Traffic prediction.

NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.

Block Diagram

Specifications

Hardware Requirements:

  • Raspberry Pi
  • Micro SD card
  • LED’s
  • Resistors
  • Camera
  • 5V Adapter   

Software Requirements:

  • NOOBS Software
  • VNC Viewer
  • Python3 IDLE
  • Fritzing
  • Third Party Server

Learning Outcomes

  • Raspberry Pi Pin diagram and Architecture
  • How to install NOOBS Software
  • Setting up and Installation procedures for Raspberry Pi
  • Introduction to Python3 IDLE
  • Commands in Python
  • How to install Libraries for camera?
  • Basic coding in Python
  • How to interface LED’s with Raspberry Pi?
  • How to interface camera with Raspberry Pi?
  • Introduction to IOT?
  • Hoe to upload the data to thingspeak Server?
  • About Project Development Life Cycle:
    • Planning and Requirement Gathering( software’s, Tools, Hardware components, etc.,)
    • Schematic preparation 
    • Code development and debugging
    • Hardware development and debugging
    • Development of the Project and Output testing
  • Practical exposure to:
    • Hardware and software tools.
    • Solution providing for real time problems.
    • Working with team/ individual.
    • Work on Creative ideas.
  • Project development Skills
    • Problem analyzing skills
    • Problem solving skills
    • Creativity and imaginary skills
    • Programming skills
    • Deployment
    • Testing skills
    • Debugging skills
    • Project presentation skills
    • Thesis writing skills

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