Analysis of Reinforcement Learning in Autonomous Vehicles

被引：1

作者：

Jebessa, Estephanos ^{[1
]}

Olana, Kidus ^{[1
]}

Getachew, Kidus ^{[1
]}

Isteefanos, Stuart ^{[1
]}

Mohd, Tauheed Khan ^{[1
]}

机构：

[1] Augustana Coll, Math & Comp Sci, Rock Isl, IL 61201 USA

来源：

2022 IEEE 12TH ANNUAL COMPUTING AND COMMUNICATION WORKSHOP AND CONFERENCE (CCWC) | 2022年

关键词：

reinforcement learning; smart cars; autonomous vehicles;

D O I：

10.1109/CCWC54503.2022.9720883

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

This paper takes a look at the mechanisms by which autonomous vehicles operate: reinforcement learning in particular. Machine learning techniques used by companies such as Waymo, Tesla, and GM have allowed them to produce high end autonomous driving systems. This paper reviews the reinforcement learning techniques and algorithms used by these companies and proposes alternative solutions to the problems faced by most of their vehicles. Moreover, this paper contains an in-depth analysis of the Q learning technique used by autonomous vehicles.

引用

页码：87 / 91

页数：5

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