Autonomous Driving Control Using End-to-End Deep Learning
Myoung‐jae Lee, Young-Guk Ha
Abstract
With the development of the artificial intelligence technology, various industries have developed. Among them, the autonomous vehicle industry has developed considerably, and researches has been carried out actively on self-driving control systems using artificial intelligence. Recently, studies have been conducted on the use of image-based end-to-end deep learning to control autonomous driving systems. An image-based end-to-end autonomous system can be configured at a low cost, in a simple system that omits complex processes. This system receives images as the input and outputs control signals. In this paper, we propose an autonomous driving control system by using end-to-end deep learning.
Topics & Concepts
End-to-end principleDeep learningComputer scienceArtificial intelligenceControl systemControl (management)Control engineeringArtificial neural networkEngineeringElectrical engineeringAdvanced Neural Network ApplicationsAutonomous Vehicle Technology and SafetyVideo Surveillance and Tracking Methods