Autonomous drifting using reinforcement learning

被引：0

作者：

Orgován L. ^{[1
]}

Bécsi T. ^{[1
]}

Aradi S. ^{[1
]}

机构：

[1] Department of Control for Transportation and Vehicle Systems, Faculty of Transportation Engineering and Vehicle Engineering, Budapest University of Technology and Economics, Műegyetem rkp. 3, Budapest

来源：

Periodica Polytechnica Transportation Engineering | 2021年 / 49卷 / 03期

关键词：

Autonomous driving; Drifting; Machine learning; Reinforcement learning;

D O I：

10.3311/PPTR.18581

中图分类号：

学科分类号：

摘要：

Autonomous vehicles or self-driving cars are prevalent nowadays, many vehicle manufacturers, and other tech companies are trying to develop autonomous vehicles. One major goal of the self-driving algorithms is to perform manoeuvres safely, even when some anomaly arises. To solve these kinds of complex issues, Artificial Intelligence and Machine Learning methods are used. One of these motion planning problems is when the tires lose their grip on the road, an autonomous vehicle should handle this situation. Thus the paper provides an Autonomous Drifting algorithm using Reinforcement Learning. The algorithm is based on a model-free learning algorithm, Twin Delayed Deep Deterministic Policy Gradients (TD3). The model is trained on six different tracks in a simulator, which is developed specifically for autonomous driving systems; namely CARLA. © 2021 Budapest University of Technology and Economics. All rights reserved.

引用

页码：292 / 300

页数：8

共 11 条

[1]

Achiam J., Deep Deterministic Policy Gradient, (2018)

[2]

Achiam J., Twin Delayed DDPG, (2019)

[3]

Aradi S., Survey of Deep Reinforcement Learning for Motion Planning of Autonomous Vehicles, (2020)

[4]

Cai P., Mei X., Tai L., Sun Y., Liu M., High-SpeedAutonomous Drifting With Deep Reinforcement Learning, IEEE Robotics and Automation Letters, 5, 2, pp. 1247-1254, (2020)

[5]

"1st. World and client, (2020)

[6]

Synchrony and time-step", (2020)

[7]

"3rd. Maps and navigation, (2020)

[8]

"Python API reference, (2020)

[9]

Hindiyeh R. Y., Dynamics and control of drifting in automobiles, (2013)

[10]

Lillicrap P. T., Hunt J. J., Pritzel A., Heess N., Erez T., Tassa Y., Silver D., Wierstra D., Continuous control with deep reinforcement learning, (2019)

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