OTFS-Assisted Sensing Adaptive Cruise Control for Highways: A Reinforcement Learning Approach
In this paper, we propose a novel channel estimation approach and driving decision method for adaptive cruise control (ACC) systems for vehicular networks, leveraging the properties of deep learning, reinforcement learning, and orthogonal time frequency space (OTFS) modulation. To achieve that, we p...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2025-01-01
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| Series: | IEEE Open Journal of Vehicular Technology |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11016009/ |
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| _version_ | 1849228538317635584 |
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| author | Yulin Liu Xiaoqi Zhang Jun Wu Qingqing Cheng |
| author_facet | Yulin Liu Xiaoqi Zhang Jun Wu Qingqing Cheng |
| author_sort | Yulin Liu |
| collection | DOAJ |
| description | In this paper, we propose a novel channel estimation approach and driving decision method for adaptive cruise control (ACC) systems for vehicular networks, leveraging the properties of deep learning, reinforcement learning, and orthogonal time frequency space (OTFS) modulation. To achieve that, we propose to leverage deep learning (DL) to estimate motion parameters. Subsequently, we develop a reinforcement learning method to process the obtained target motion information to enable adaptive vehicle-following strategies. This ensures robust decision-making and precise control under dynamic and uncertain driving conditions, achieving superior performance in terms of both accuracy and reliability. |
| format | Article |
| id | doaj-art-c172fdd4d7c44e2d8468cc4a1212cc2d |
| institution | Kabale University |
| issn | 2644-1330 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Open Journal of Vehicular Technology |
| spelling | doaj-art-c172fdd4d7c44e2d8468cc4a1212cc2d2025-08-22T23:17:32ZengIEEEIEEE Open Journal of Vehicular Technology2644-13302025-01-0161861187110.1109/OJVT.2025.357422311016009OTFS-Assisted Sensing Adaptive Cruise Control for Highways: A Reinforcement Learning ApproachYulin Liu0https://orcid.org/0009-0003-1536-5547Xiaoqi Zhang1https://orcid.org/0009-0004-5034-0959Jun Wu2https://orcid.org/0000-0001-9424-1056Qingqing Cheng3https://orcid.org/0000-0003-2664-5176Department of Electrical, Electronic Engineering, Southern University of Science, Technology, Shenzhen, ChinaSchool of Electrical, Data Engineering, University of Technology Sydney, Sydney, NSW, AustraliaSchool of Automation and Intelligent Manufacturing, Southern University of Science, Technology, Shenzhen, ChinaSchool of Electrical Engineering and Robotics, Queensland University of Technology, Brisbane, QLD, AustraliaIn this paper, we propose a novel channel estimation approach and driving decision method for adaptive cruise control (ACC) systems for vehicular networks, leveraging the properties of deep learning, reinforcement learning, and orthogonal time frequency space (OTFS) modulation. To achieve that, we propose to leverage deep learning (DL) to estimate motion parameters. Subsequently, we develop a reinforcement learning method to process the obtained target motion information to enable adaptive vehicle-following strategies. This ensures robust decision-making and precise control under dynamic and uncertain driving conditions, achieving superior performance in terms of both accuracy and reliability.https://ieeexplore.ieee.org/document/11016009/ACCdeep learningOTFSreinforcement learning |
| spellingShingle | Yulin Liu Xiaoqi Zhang Jun Wu Qingqing Cheng OTFS-Assisted Sensing Adaptive Cruise Control for Highways: A Reinforcement Learning Approach IEEE Open Journal of Vehicular Technology ACC deep learning OTFS reinforcement learning |
| title | OTFS-Assisted Sensing Adaptive Cruise Control for Highways: A Reinforcement Learning Approach |
| title_full | OTFS-Assisted Sensing Adaptive Cruise Control for Highways: A Reinforcement Learning Approach |
| title_fullStr | OTFS-Assisted Sensing Adaptive Cruise Control for Highways: A Reinforcement Learning Approach |
| title_full_unstemmed | OTFS-Assisted Sensing Adaptive Cruise Control for Highways: A Reinforcement Learning Approach |
| title_short | OTFS-Assisted Sensing Adaptive Cruise Control for Highways: A Reinforcement Learning Approach |
| title_sort | otfs assisted sensing adaptive cruise control for highways a reinforcement learning approach |
| topic | ACC deep learning OTFS reinforcement learning |
| url | https://ieeexplore.ieee.org/document/11016009/ |
| work_keys_str_mv | AT yulinliu otfsassistedsensingadaptivecruisecontrolforhighwaysareinforcementlearningapproach AT xiaoqizhang otfsassistedsensingadaptivecruisecontrolforhighwaysareinforcementlearningapproach AT junwu otfsassistedsensingadaptivecruisecontrolforhighwaysareinforcementlearningapproach AT qingqingcheng otfsassistedsensingadaptivecruisecontrolforhighwaysareinforcementlearningapproach |