| Self-driving car using CNN Deep learning model |
| Paper ID : 1191-IUGRC6 |
| Authors |
|
Amin S. Ibrahim *1, Adel Refky1, A. M. Abdel Ghany2, • Omer Mohamed Ibrahim3, Ahmed Mohamed Na'eem3, Andrew Samy Hanna3, Shady Mohamed Ezz4, Mohamed Reda Mohamed4, Hassan Mohamed Abdel Hameed3, Felopateer Sanad3, Hossam Ibrahim Hassan3 1Department of Electronics and Communications Engineering, Thebes Higher Institute for Engineering, Cairo, Egypt 2Department of Electric Power and Machines, Thebes Higher Institute for Engineering, Cairo, Egypt 3Thebes Higher Institute for Engineering, Egypt 4Thebes Higher Institute for Engineering, Egypt, |
| 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 unrespecting 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 porotype 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 |
| Artificial Intelligent, Deep Learning, CNN model, Self-driving Car |
| Status: Accepted |