Exploring Applications of Deep Reinforcement Learning for Real-world Autonomous Driving Systems

Victor Talpaert, Ibrahim Sobh, B. Kiran, Patrick Mannion, Senthil Yogamani, Ahmad El-Sallab, Patrick Perez

Abstract

Deep Reinforcement Learning (DRL) has become increasingly powerful in recent years, with notable achievements such as Deepmind’s AlphaGo. It has been successfully deployed in commercial vehicles like Mobileye’s path planning system. However, a vast majority of work on DRL is focused on toy examples in controlled synthetic car simulator environments such as TORCS and CARLA. In general, DRL is still at its infancy in terms of usability in real-world applications. Our goal in this paper is to encourage real-world deployment of DRL in various autonomous driving (AD) applications. We first provide an overview of the tasks in autonomous driving systems, reinforcement learning algorithms and applications of DRL to AD systems. We then discuss the challenges which must be addressed to enable further progress towards real-world deployment.

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Paper Citation


in Harvard Style

Talpaert V., Sobh I., Kiran B., Mannion P., Yogamani S., El-Sallab A. and Perez P. (2019). Exploring Applications of Deep Reinforcement Learning for Real-world Autonomous Driving Systems.In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, ISBN 978-989-758-354-4, pages 564-572. DOI: 10.5220/0007520305640572


in Bibtex Style

@conference{visapp19,
author={Victor Talpaert and Ibrahim Sobh and B. Kiran and Patrick Mannion and Senthil Yogamani and Ahmad El-Sallab and Patrick Perez},
title={Exploring Applications of Deep Reinforcement Learning for Real-world Autonomous Driving Systems},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP,},
year={2019},
pages={564-572},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007520305640572},
isbn={978-989-758-354-4},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP,
TI - Exploring Applications of Deep Reinforcement Learning for Real-world Autonomous Driving Systems
SN - 978-989-758-354-4
AU - Talpaert V.
AU - Sobh I.
AU - Kiran B.
AU - Mannion P.
AU - Yogamani S.
AU - El-Sallab A.
AU - Perez P.
PY - 2019
SP - 564
EP - 572
DO - 10.5220/0007520305640572