Mr. Ali Almadwami Profile

Ali Almadwami

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Proceedings Article | 9 August 2023 Paper

A convolutional neural network approach for optimal steering control of self-driving cars

Tameem Hezam, Mohammed Al Mahbashi, Hashem Almadwami, Ali Almadwami

Proceedings Volume 12782, 127820J (2023) https://doi.org/10.1117/12.3001346

KEYWORDS: Machine learning, Education and training, Roads, Cameras, Autonomous driving, Convolutional neural networks, Autonomous vehicles, Video, Unmanned vehicles, Visualization

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The end-to-end learning framework for autonomous cars has attracted considerable interest in recent years from both industry and academia. To control an autonomous car, this approach requires developing a model that links sensory perception, such as picture frames from a camcorder, to learn the optimal and safe driving actions. To develop a completely automated driving, it is possible to use professional driver experience more efficiently by using the end-to-end learning approach rather than spending a significant amount of money on labelling like bounding boxes for things. The conventional self-driving system, which typically consists of detection, positioning, mapping, and route planning manually fails to perform well with dynamic autonomous vehicles. We proposed a Convolutional Neural Network (CNN) framework for learning the autonomous driving to convert front-facing camera data from raw pixels and learn the steering commands. This end-to-end strategy has shown very promising results compared to the traditional self-driving models. The proposed CNN framework learns to intelligently drive in traffic on local roads with or without lane markings, on motorways, and with the least amount of training data from experts. Additionally, it also works smartly in places with obscure visual cues, including parking lots and gravel roadways. The system spontaneously picks up internal demonstrations of the essential processing phases, like identifying convenient road objects, by learning the human steering angle as the training input.

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