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A Reinforcement Learning Assisted Relative Distance based MAC in Vehicular Networks
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Publication Year
2023-01-01
Journal
5th International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2023
Publisher
Institute of Electrical and Electronics Engineers Inc.
Citation
5th International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2023, pp.371-374
Keyword
Merging CollisionReinforcement LearningTDMAVehicular Networking
Mesh Keyword
Collisions avoidanceDistance-basedMerging collisionPerformanceReinforcement learningsRelative distancesSafety messagesVehicle to vehiclesVehicular networkingsVehicular networks
All Science Classification Codes (ASJC)
Computer Networks and CommunicationsInformation SystemsSignal ProcessingDecision Sciences (miscellaneous)Information Systems and ManagementArtificial Intelligence
Abstract
Many efforts have been done to increase the performance of vehicle-to-vehicle (V2V) services, such as basic safety message (BSM) and collision avoidance warning. However, high dynamics, such as topology and channel condition, still pose big challenges to resource allocation tasks in vehicular networks. A previous work, relative distance based MAC [1], is proposed to address merging collision. The dynamics can not be fully addressed because thresholds are used. Therefore, we intuitively adapt a dueling deep Q-network [2] to tune the threshold based on the aforementioned work to further address merging collision. The simulation results demonstrate the improvement of the proposed algorithm.
Language
eng
URI
https://aurora.ajou.ac.kr/handle/2018.oak/36946
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85151982547&origin=inward
DOI
https://doi.org/10.1109/icaiic57133.2023.10067126
Journal URL
http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=10066849
Type
Conference
Funding
ACKNOWLEDGMENT This work was supported by the BK21 FOUR program of the National Research Foundation of Korea funded by the Ministry of Education(NRF5199991014091).
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Choi, Youngjune Image
Choi, Youngjune최영준
Department of Software and Computer Engineering
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