Automation has created a bigger hype in the electronics. The major reason for this hype is automation provides greater advantages like accuracy, energy conversation, reliability and more over the automated systems do not require any human attention. Any one of the requirements stated above demands for the design of an automated device. The energy conversation is very important in the current scenario and should be done to a maximum extent where ever it is possible. Energy can be effectively conserved if we can control the traffic lights on the highways by glowing them according with time delay. So in this situation we should think about a system which is capable of sensing the traffic density and automatically should manage to control the traffic levels by increasing the time delay for the green signal to the roads which are with heavy traffic. The aim of this project is to build a traffic signal control system based on density using image processing with camera and raspberry pi3 A+ processor. The program running inside microcontroller which is attached to the raspberry pi is going to control the traffic lights. In this pi camera is mounted on traffic signals with servo motor which is interfaced to the raspberry for continuously monitoring of traffic density using tensor flow CNN and process this data to PIC microcontroller then PIC Microcontroller control the traffic signal accordingly. PIC micro controller used here is programmed by Embedded C language. The SD card is a key part of the Raspberry Pi; it provides the initial storage for the Operating System and files. Storage can be extended through many types of USB connected peripherals.

   

The main objective of this project is:  

1. Automatic traffic lights control.
2. Traffic density can be known by using pi camera.
3. Using image processing to identify the traffic density.
4. Using Raspberrypi3, PIC Microcontroller to achieve this task.

  The major building blocks of this project are:  

1. Regulated Power Supply.
2. PIC Microcontroller.
3. Crystal Oscillator.
4. Reset.
5. LED Indicators.
6. Traffic signals.
7. Raspberry pi3.
8. Pi camera.

  Software’s used:  

1. PIC-C compiler for Embedded C programming.
2. PIC kit 2 programmer for dumping code into Micro controller.
3. Express SCH for Circuit design.
4. Linux OS, Python language.
5. Image processing technology.

 

Regulated Power Supply:

   

Block Diagram:      

 

video: