Automated Car

Project Title

Automated Car

Project Area of Specialization RoboticsProject Summary

The project is based on AI OpenCV Neural Network which will alow the Robotic CAR it self to operate in real time environment. The Robotic CAR will be able to reach its destination from the source, keeping all the necessary environmental conditions in view. 

1. It will adjust it self to avoide any collision
2. it will detect objects, signs and traffic lights
3. It will self drive on track by monitoring lane markings 

This project will consits of three main subsystems:

1. Input unit (camera & sensors)
2. Processing unit (computer or microcontroller)
3. Control unit (motors, chassis, wheels etc.)

Project Objectives

The objectives of the this project are as following:

1. Self-driving on track with lane switching.
2. Sign detection (stop, slow), signal/traffic light detection, object detection.
3. 360° collision avoidance.

Project Implementation Method

Algorithms and techniques that we will need to accomplish this system are

1. Machine learning algorithms using python3.
2. AI Neural Networks which is very much important for this system because once the network is trained, it only needs to load trained parameters afterwards. Which helps the prediction process work very fast.
3. Object detection such as stop sign and traffic light detection.
4. Some sensors like distance measurement ultrasonic sensors, cameras, lights etc. 

Project Implementation Method 

This system or prototype is divided into three sub-systems

1- Input Unit

Input unit includes Raspberry Pi board (model B+), attached with a pi camera module and different sensors are used to collect input data. Client program run on Raspberry Pi for streaming colour video. In order to achieve low latency video streaming, video can be scaled down to 320×240 resolution.

2- Processing Unit

The processing unit (computer) will handle multiple tasks like receiving data from Raspberry Pi, neural network training and prediction (steering), object detection (stop sign and traffic light), distance measurement (monocular vision), and sending instructions to Arduino through USB connection.

3- Control Unit

The prototype that we will use in this project will have an on/off switch type controller. When a button is pressed, the resistance between the relevant chip pin and ground is zero. Thus, an Arduino board is used to simulate button-press actions. Arduino pins will be used to connect four chip pins on the controller, corresponding to forward, reverse, left and right actions respectively. Arduino pins sending LOW signal indicates grounding the chip pins of the controller, on the other hand sending HIGH signal indicates the resistance between chip pins and ground remain unchanged. The Arduino is connected to the computer via USB. The computer will output commands to Arduino using serial interface, and then the Arduino will read the commands and writes out LOW or HIGH signals, simulating button-press actions to drive the prototype.

Benefits of the Project

Benefits of the Project

1. Less Human interaction while driving.
2. Provide more efficient driving experience.
3. Security and safety measures.
4. Environmental friendly.
5. Smarter then humans.
6. Time and cost deduction 

Technical Details of Final Deliverable

Resource Requirement

1. Knowledge about Python3.
2. Raspberry Pi.              (4GB)
3. Arduino.                      (UNO 3)
4. Sensors.
5. Deep understanding of AI Neural Networks.
6. Digital Image Processing (DIP).

Tools / Technology

1. Microcontrollers                                                 
2. Sensors                                                              
3. Required hardware (motor, chassis etc)                        

Final Deliverable of the Project Hardware SystemCore Industry TransportationOther Industries Manufacturing , Security Core Technology RoboticsOther TechnologiesSustainable Development Goals Industry, Innovation and Infrastructure, Partnerships to achieve the GoalRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	32460
Raspberry Pi 4 (4GB RAM)	Equipment	1	17500	17500
Raspberry Pi Heatsink Cooler	Miscellaneous	1	150	150
Raspberry Pi 4 HDMI Cable	Equipment	1	300	300
8MP Raspberry Pi Camera Module V2	Equipment	1	4800	4800
Class 10 SanDisk 32GB Ultra Micro SD Card	Equipment	1	1500	1500
Raspberry Pi 4 Case with fan fitting	Miscellaneous	1	350	350
10000mAH PowerBank	Equipment	1	2500	2500
Arduino Uno R3 with cable	Equipment	1	800	800
IR infrared obstacle avoidance sensor	Equipment	4	100	400
Ultrasonic Sensor	Equipment	4	150	600
4WD smart robot car chassis kit	Equipment	1	1300	1300
TCRT 5000 line tracking sensor module	Equipment	2	100	200
L293D Motor Driver Shield	Equipment	1	400	400
Traffic Light LED Module	Equipment	1	100	100
Jumping Wires (M-M, M-F)	Miscellaneous	2	200	400
Card Board Sheet 4x4	Miscellaneous	6	160	960
Chart Papers (White and Black)	Miscellaneous	10	20	200