A vehicle capable of using sensors to detect and control its driving actions is called an autonomous vehicle. The development of autonomous vehicles caters to many application areas in the technological advancement of society. This research paper shows a demonstration and implementation of an autonomous vehicle based on a convolutional neural network. The vehicle uses a 1/10th scale RC car as its primary base for the system control with the camera as its primary input. For the computing platform, a Raspberry Pi 4 microprocessor board is used. To enhance the capabilities, the ultrasonic sensor has been implemented in the system as well. The unique aspect of this project is the system design, the CAD modeling, and the track built used to train and test the self-driving capability of the car. The CNN model and the software algorithm also are exclusive to this research project. This research has potential in a variety of application areas in education and also for robotics and autonomous car enthusiasts.
|Number of pages||17|
|Journal||International Journal on Smart Sensing and Intelligent Systems|
|Publication status||Published - Jan 2020|
Bibliographical noteCopyright the Author(s) 2020. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.
- Autonomous vehicle
- Convolutional neural network
- Raspberry pi 4
- Ultrasonic sensor