Self-Driving Car Based CNN Deep Learning Model

Ibrahim, Amin S.; Refky, Adel; M. Abdelghany, Abdelghany

doi:10.21608/ijaebs.2023.208574.1081

Self-Driving Car Based CNN Deep Learning Model

Document Type : Original Article

Authors

¹ Electronic and communication department, Thebes Higher Institute for Engineering, Cairo, Egypt

² Electronics and communication Department, Thebes Higher Institute for Engineering, Egypt, Cairo

³ Faculty of Engineering Helwan University, Department of Electric Power and Machines, Egypt, Cairo

10.21608/ijaebs.2023.208574.1081

Abstract

Artificial Intelligent (AI) technology is capable of thinking and recognizing environmental things based on the vast amount of historical training data. AI technology can mimic the human brain with large and complicated computations and short processing time. One of the main challenges in our daily life is the rapid growth of accidents and deaths due to the wrong driving by citizens and un- respecting the traffic rules. Thus, AI technology is coming as a solution to solve this issue through the so-called self-driving car. In this paper, we proposed a self-driving car based on the Convolutional Neural Network (CNN) deep learning model in AI technology. The paper designed and implemented a self-driving car prototype to prove the concept and validate our experimental self-driving car model. It is remarked that a prototype is successfully trained and tested about 5000 images with very low training and validation loss of less than 0.05 and 0.12 respectively.

Keywords