Automated Lane Change Decision Making using Deep Reinforcement Learning in Dynamic and Uncertain Highway Environment

Ali Alizadeh; Majid Moghadam; Yunus Bicer; Nazim Kemal Ure; Ugur Yavas; Can Kurtulus

doi:10.1109/ITSC.2019.8917192

Automated Lane Change Decision Making using Deep Reinforcement Learning in Dynamic and Uncertain Highway Environment

Ali Alizadeh, Majid Moghadam, Yunus Bicer, Nazim Kemal Ure, Ugur Yavas, Can Kurtulus

Department of Artificial Intelligence and Data Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

110 Citations (Scopus)

Abstract

Autonomous lane changing is a critical feature for advanced autonomous driving systems, that involves several challenges such as uncertainty in other driver's behaviors and the trade-off between safety and agility. In this work, we develop a novel simulation environment that emulates these challenges and train a deep reinforcement learning agent that yields consistent performance in a variety of dynamic and uncertain traffic scenarios. Results show that the proposed data-driven approach performs significantly better in noisy environments compared to methods that rely solely on heuristics.

Original language	English
Title of host publication	2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1399-1404
Number of pages	6
ISBN (Electronic)	9781538670248
DOIs	https://doi.org/10.1109/ITSC.2019.8917192
Publication status	Published - Oct 2019
Event	2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019 - Auckland, New Zealand Duration: 27 Oct 2019 → 30 Oct 2019

Publication series

Name	2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019

Conference

Conference	2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019
Country/Territory	New Zealand
City	Auckland
Period	27/10/19 → 30/10/19

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

Access to Document

10.1109/ITSC.2019.8917192

Cite this

Alizadeh, A., Moghadam, M., Bicer, Y., Ure, N. K., Yavas, U., & Kurtulus, C. (2019). Automated Lane Change Decision Making using Deep Reinforcement Learning in Dynamic and Uncertain Highway Environment. In 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019 (pp. 1399-1404). Article 8917192 (2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ITSC.2019.8917192

Alizadeh, Ali ; Moghadam, Majid ; Bicer, Yunus et al. / Automated Lane Change Decision Making using Deep Reinforcement Learning in Dynamic and Uncertain Highway Environment. 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 1399-1404 (2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019).

@inproceedings{1e08acaeec094717aaa16a5e17735136,

title = "Automated Lane Change Decision Making using Deep Reinforcement Learning in Dynamic and Uncertain Highway Environment",

abstract = "Autonomous lane changing is a critical feature for advanced autonomous driving systems, that involves several challenges such as uncertainty in other driver's behaviors and the trade-off between safety and agility. In this work, we develop a novel simulation environment that emulates these challenges and train a deep reinforcement learning agent that yields consistent performance in a variety of dynamic and uncertain traffic scenarios. Results show that the proposed data-driven approach performs significantly better in noisy environments compared to methods that rely solely on heuristics.",

author = "Ali Alizadeh and Majid Moghadam and Yunus Bicer and Ure, \{Nazim Kemal\} and Ugur Yavas and Can Kurtulus",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019 ; Conference date: 27-10-2019 Through 30-10-2019",

year = "2019",

month = oct,

doi = "10.1109/ITSC.2019.8917192",

language = "English",

series = "2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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booktitle = "2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019",

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Alizadeh, A, Moghadam, M, Bicer, Y, Ure, NK, Yavas, U & Kurtulus, C 2019, Automated Lane Change Decision Making using Deep Reinforcement Learning in Dynamic and Uncertain Highway Environment. in 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019., 8917192, 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019, Institute of Electrical and Electronics Engineers Inc., pp. 1399-1404, 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019, Auckland, New Zealand, 27/10/19. https://doi.org/10.1109/ITSC.2019.8917192

Automated Lane Change Decision Making using Deep Reinforcement Learning in Dynamic and Uncertain Highway Environment. / Alizadeh, Ali; Moghadam, Majid; Bicer, Yunus et al.
2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019. Institute of Electrical and Electronics Engineers Inc., 2019. p. 1399-1404 8917192 (2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Moghadam, Majid

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AU - Yavas, Ugur

AU - Kurtulus, Can

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AB - Autonomous lane changing is a critical feature for advanced autonomous driving systems, that involves several challenges such as uncertainty in other driver's behaviors and the trade-off between safety and agility. In this work, we develop a novel simulation environment that emulates these challenges and train a deep reinforcement learning agent that yields consistent performance in a variety of dynamic and uncertain traffic scenarios. Results show that the proposed data-driven approach performs significantly better in noisy environments compared to methods that rely solely on heuristics.

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Alizadeh A, Moghadam M, Bicer Y, Ure NK, Yavas U, Kurtulus C. Automated Lane Change Decision Making using Deep Reinforcement Learning in Dynamic and Uncertain Highway Environment. In 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 1399-1404. 8917192. (2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019). doi: 10.1109/ITSC.2019.8917192

Automated Lane Change Decision Making using Deep Reinforcement Learning in Dynamic and Uncertain Highway Environment

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