Cloud-Edge-Terminal Collaborative AIGC for Autonomous Driving
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arXiv
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| Hauptverfasser: | , , , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| _version_ | 1866914855709048832 |
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| author | Zhang, Jianan Wei, Zhiwei Liu, Boxun Wang, Xiayi Yu, Yong Zhang, Rongqing |
| author_facet | Zhang, Jianan Wei, Zhiwei Liu, Boxun Wang, Xiayi Yu, Yong Zhang, Rongqing |
| contents | In dynamic autonomous driving environment, Artificial Intelligence-Generated Content (AIGC) technology can supplement vehicle perception and decision making by leveraging models' generative and predictive capabilities, and has the potential to enhance motion planning, trajectory prediction and traffic simulation. This article proposes a cloud-edge-terminal collaborative architecture to support AIGC for autonomous driving. By delving into the unique properties of AIGC services, this article initiates the attempts to construct mutually supportive AIGC and network systems for autonomous driving, including communication, storage and computation resource allocation schemes to support AIGC services, and leveraging AIGC to assist system design and resource management. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_01956 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Cloud-Edge-Terminal Collaborative AIGC for Autonomous Driving Zhang, Jianan Wei, Zhiwei Liu, Boxun Wang, Xiayi Yu, Yong Zhang, Rongqing Systems and Control Robotics In dynamic autonomous driving environment, Artificial Intelligence-Generated Content (AIGC) technology can supplement vehicle perception and decision making by leveraging models' generative and predictive capabilities, and has the potential to enhance motion planning, trajectory prediction and traffic simulation. This article proposes a cloud-edge-terminal collaborative architecture to support AIGC for autonomous driving. By delving into the unique properties of AIGC services, this article initiates the attempts to construct mutually supportive AIGC and network systems for autonomous driving, including communication, storage and computation resource allocation schemes to support AIGC services, and leveraging AIGC to assist system design and resource management. |
| title | Cloud-Edge-Terminal Collaborative AIGC for Autonomous Driving |
| topic | Systems and Control Robotics |
| url | https://arxiv.org/abs/2407.01956 |