Skip to content

The Traffic Light Control System aims to develop an advanced real-time responsive traffic management solution. This initiative focuses on reducing the time spent by individuals at traffic signals, thereby enhancing road safety and efficiency.

License

saleemhamo/traffic-light-system

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Traffic Light Control System Logo

Pioneering Traffic Management Solutions for Urban Mobility 🚦

Instagram Badge Latest Release Badge Project Badge Issues Badge Pull Requests Badge

Traffic Light Control System

Welcome to the Traffic Light Control System project, an innovative solution to revolutionize urban traffic management across the UK. Our system intelligently optimizes traffic flow and enhances pedestrian safety using cutting-edge technology, all powered by a Raspberry Pi. By analyzing real-time traffic and pedestrian data, we dynamically adjust traffic signals to reduce waiting times and improve the overall safety of road intersections.

Getting Started with Installation

Step 1: Update Your Raspberry Pi

Before installing any new software, please ensure your Raspberry Pi is up-to-date with the latest system updates. This can help prevent compatibility issues and ensure the system runs smoothly.

sudo apt-get update
sudo apt-get upgrade

Step 2: Install PiGPIO

PiGPIO is essential for controlling the GPIO (General Purpose Input Output) pins on the Raspberry Pi. Install it using the following commands:

wget https://github.com/joan2937/pigpio/archive/master.zip
unzip master.zip
cd pigpio-master
make
sudo make install

Step 3: Install Necessary Libraries

Several libraries are required for the Traffic Light Control System to function properly, including Boost, OpenCV for image processing, and GStreamer for handling media.

  • Install Boost Libraries:

    sudo apt-get install libboost-all-dev
  • Install OpenCV: This library is used for processing images and videos, which is crucial for detecting vehicles and pedestrians.

    sudo apt-get install libopencv-dev libcamera-dev
  • Install GStreamer: GStreamer is used for handling video streams which is vital for any camera-based monitoring.

    sudo apt-get install gstreamer1.0-tools gstreamer1.0-plugins-base gstreamer1.0-plugins-good gstreamer1.0-plugins-bad gstreamer1.0-plugins-ugly gstreamer1.0-libav

Step 4: Clone and Set Up the Project

Clone the repository and prepare the software environment.

git clone https://github.com/saleemhamo/traffic-light-system.git
cd traffic-light-system
cmake .
make
sudo ./CrossGuard

Note

The information provided in these steps is subject to change as the development progresses. We welcome contributions from the community to help improve and expand the functionality of the Traffic Light Control System.

Project Components

This project is a blend of hardware (HW) and software (SW) components, working harmoniously to bring about a seamless traffic management experience soon to be deployed.

Hardware Setup

The heart of our system lies in its carefully designed circuitry and the selection of equipment:

  • Raspberry Pi: Acts as the central processing unit of our traffic control system.
  • Sensors: For real-time traffic and pedestrian demand detection.
  • Signal Lights: To visually communicate with traffic participants.

For a detailed overview of the circuit design and equipment, please refer to our Wiki page on hardware setup.

Software architecture

Our software is developed with efficiency and scalability in mind, featuring:

  • Dynamic Signal Adjustment Algorithms: To process data from various sensors and adjust traffic lights accordingly.
  • User-Friendly Interface: For easy system setup and monitoring.

The complete design document can be found in our GitHub Wiki under the Design Document section.

Note

The camera functionality in the Traffic Light Control System is made possible by the work of the community, particularly through the efforts of Bernd Porr, who provided a convenient interface for integrating libcamera with OpenCV. His repository libcamera2opencv facilitated the integration of camera functionality with Qt without much hassle.


Tip

Stay updated with the latest developments and share your feedback with us through our Instagram profile. We're excited to see how our system enhances urban traffic management for communities by dramatically improving pedestrian safety and slashing those seemingly endless waiting times at crossing!

Embrace the future of traffic control with our Traffic Light Control System, where innovation meets practicality.

About

The Traffic Light Control System aims to develop an advanced real-time responsive traffic management solution. This initiative focuses on reducing the time spent by individuals at traffic signals, thereby enhancing road safety and efficiency.

Topics

Resources

License

Stars

Watchers

Forks

Contributors 4

  •  
  •  
  •  
  •