Autonomous Car Using Raspberry PI

Project Title

Autonomous Car Using Raspberry PI

Project Area of Specialization Artificial IntelligenceProject Summary

This project aims to represent a mini version of self-driving car using IOT with raspberry pi and Arduino UNO working as a main processor chip, the 8mp high resolution pi camera will provide the necessary information and the raspberry pi will analyze the data(samples) and it will get trained in pi with neural network and machine learning algorithm which would result in detecting road lanes, Traffic Light Detection, Stop Sign detection, static obstacle detection and overtaking. In addition to these features the car will overtake with proper LED indications if it comes across an obstacle. Before this we will develop simulation to navigate a self-driving car around a racetrack in the CARLA simulation environment. we will try to implement advance level of Robotics concept like construct longitudinal and lateral dynamic models for a vehicle and create controllers that regulate speed and path tracking performance using Python.

Project Objectives

The existing system of driving a car is the manual one. From steering to speed control and lane detection, everything is controlled by human. And humans are erroneous leading to fatal accidents.

The main purpose of our project is to automate the driving system through image processing and machine learning so that it could drive the car along the lane and detect any obstacle coming in its way, detect traffic signal and detect traffic sign thus reducing the chances of accidents.

Project Implementation Method

To develop a proof of concept of a real time Autonomous Car a complete working system will be implemented using a small-scale Autonomous Car prototype.

1. Implementation of Lane Tracking will be by using Computer Vision Techniques.
2. To detect Obstacle, Traffic light and traffic signs like stop sign we will use Machine Learning.
3. We will design LED dynamic turn signal indicators to improve aesthetic of our hardware.

Benefits of the Project

1. To make cars safer, drivers more aware, and accidents less likely.
2.  The technology appears close to maturity and commercial introduction.
3. Reducing the opportunity for human error

Technical Details of Final Deliverable

1)Input Module

This module consists of a camera module. Data will be gathered continuously through camera and user will be viewing it live on raspberry screen. Data gathered from camera will be used for

• Line Tracking
• Obstacle overtaking
• Traffic light recognition
• Traffic Sign Detection

2. Processing Module

This module Raspberry PI is responsible for:

 Receiving data from camera and perform

• Sending Instruction to Arduino
• Line Tracking using Computer Vision Techniques
• Obstacle Detection using Neural Network Prediction
• Traffic light recognition using Neural Network Prediction
• Traffic Sign Detection using Neural Network Prediction

3. Control Module

• Control of Car Motors like move
  • Forward
  • Backward
  • Leftward
  • Rightward

Will controlled by Arduino.

Final Deliverable of the Project Hardware SystemCore Industry ITOther IndustriesCore Technology Artificial Intelligence(AI)Other Technologies Internet of Things (IoT)Sustainable Development Goals Industry, Innovation and InfrastructureRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	79140
4W RC METAL car	Equipment	1	30000	30000
Raspberry Pi v4	Equipment	1	18000	18000
Arduino uno	Equipment	1	1000	1000
USB cable Wire	Equipment	4	200	800
Raspberry pi touchscreen display	Equipment	1	7000	7000
L298D Motor Driver	Equipment	1	1000	1000
Lipo Battery	Equipment	1	12200	12200
Charger	Miscellaneous	1	4000	4000
Capacitor	Miscellaneous	5	100	500
Material for Road Trach Building	Miscellaneous	1	2000	2000
Solder	Miscellaneous	1	800	800
Silicon	Miscellaneous	1	400	400
Jumper Wires	Miscellaneous	12	120	1440