In the published article, there was an error. Algorithm 2:aloshould be.
A correction has been made to 3 Approach, 3.2 Decision making. This sentence previously stated:
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In the published article, there was an error. Algorithm 2:aloshould be.
A correction has been made to 3 Approach, 3.2 Decision making. This sentence previously stated:
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The corrected sentence appears below:
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A correction has been made to 4 MDP Formalization, 4.3 Reward. This sentence previously stated:
“For the first objective, not causing collisions and remaining within the road boundaries, we define an indicator indf signaling when the agent has failed in the following way:”
The corrected sentence appears below:
“For the first objective, not causing collisions and remaining within the road boundaries, we define an indicator f signaling when the agent has failed in the following way:”
A correction has been made to 4 MDP Formalization, 4.3 Reward. This equation previously stated:
The corrected equation appears below:
A correction has been made to 4 MDP Formalization, 4.3 Reward. This equation previously stated:
The corrected equation appears below:
A correction has been made to 4 MDP formalization, 4.3 Reward. This equation previously stated:
The corrected equation appears below:
A correction has been made to 6 Experiments and results, 6.3 Smoothness analysis. This equation previously stated:
The corrected equation appears below:
A correction has been made to 6 Experiments and results, 6.3 Smoothness analysis. This sentence previously stated:
“The results indicate that the best performance in terms of jerk is yielded when the reward function from Eq. 8 is used and when jw is assigned a value around 2. However, is important to note that the performance is not very sensitive to the value chosen for jw and performs similarly well in a range of values. It is interesting to note that when the value for jw is too low, e.g., 0.5, the agent deems the jerk-related reward component less significant which results in higher jerk values.”
The corrected sentence appears below:
“The results indicate that the best performance in terms of jerk is yielded when the reward function from Eq. 8 is used and when jrw is assigned a value around 2. However, is important to note that the performance is not very sensitive to the value chosen for jrw and performs similarly well in a range of values. It is interesting to note that when the value for jrw is too low, e.g., 0.5, the agent deems the jerk-related reward component less significant which results in higher jerk values.”
A correction has been made to Appendix, Trajectory generation details. This equation previously stated:
The corrected equation appears below:
A correction has been made to Appendix, Trajectory generation details. This equation previously stated:
The corrected equation appears below:
The authors apologize for these errors and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.
Statements
Publisher’s note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Summary
Keywords
reinforcement learning, trajectory optimization, autonomous driving, offline reinforcement learning, continuous control
Citation
Mirchevska B, Werling M and Boedecker J (2023) Corrigendum: Optimizing trajectories for highway driving with offline reinforcement learning. Front. Future Transp. 4:1320940. doi: 10.3389/ffutr.2023.1320940
Received
13 October 2023
Accepted
09 November 2023
Published
11 December 2023
Approved by
Frontiers Editorial Office, Frontiers Media SA, Switzerland
Volume
4 - 2023
Updates
Copyright
© 2023 Mirchevska, Werling and Boedecker.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Branka Mirchevska, mirchevb@informatik.uni-freiburg.de
Disclaimer
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.