Autonomous Driving in Roundabout Maneuvers Using Reinforcement Learning with Q-Learning

被引：48

作者：

Garcia Cuenca, Laura ^{[1
]}

Puertas, Enrique ^{[1
]}

Fernandez Andres, Javier ^{[1
]}

Aliane, Nourdine ^{[1
]}

机构：

[1] Univ Europea Madrid, Sch Architecture Engn & Design, Tajo S-N, Madrid 28670, Spain

来源：

ELECTRONICS | 2019年 / 8卷 / 12期

关键词：

reinforcement learning; Q-learning; autonomous driving; roundabouts; machine learning; simulation environment; driving behavior; environment perception; RECOGNITION;

D O I：

10.3390/electronics8121536

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Navigating roundabouts is a complex driving scenario for both manual and autonomous vehicles. This paper proposes an approach based on the use of the Q-learning algorithm to train an autonomous vehicle agent to learn how to appropriately navigate roundabouts. The proposed learning algorithm is implemented using the CARLA simulation environment. Several simulations are performed to train the algorithm in two scenarios: navigating a roundabout with and without surrounding traffic. The results illustrate that the Q-learning-algorithm-based vehicle agent is able to learn smooth and efficient driving to perform maneuvers within roundabouts.

引用

页数：13

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