Autonomous Driving Control Using End-to-End Deep Learning

被引：21

作者：

Lee, Myoung-jae ^{[1
]}

Ha, Young-guk ^{[1
]}

机构：

[1] Konkuk Univ, Dept Comp Sci & Engn, Seoul, South Korea

来源：

2020 IEEE INTERNATIONAL CONFERENCE ON BIG DATA AND SMART COMPUTING (BIGCOMP 2020) | 2020年

关键词：

Autonomous Vehicle; Self-Driving System; CNN; LSTM;

D O I：

10.1109/BigComp48618.2020.00-23

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

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.

引用

页码：470 / 473

页数：4