Soar: Design and Deployment of A Smart Roadside Infrastructure System for Autonomous Driving
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arXiv
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| Autores principales: | , , , , , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866914767748202496 |
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| author | Shi, Shuyao Ling, Neiwen Jiang, Zhehao Huang, Xuan He, Yuze Zhao, Xiaoguang Yang, Bufang Bian, Chen Xia, Jingfei Yan, Zhenyu Yeung, Raymond Xing, Guoliang |
| author_facet | Shi, Shuyao Ling, Neiwen Jiang, Zhehao Huang, Xuan He, Yuze Zhao, Xiaoguang Yang, Bufang Bian, Chen Xia, Jingfei Yan, Zhenyu Yeung, Raymond Xing, Guoliang |
| contents | Recently,smart roadside infrastructure (SRI) has demonstrated the potential of achieving fully autonomous driving systems. To explore the potential of infrastructure-assisted autonomous driving, this paper presents the design and deployment of Soar, the first end-to-end SRI system specifically designed to support autonomous driving systems. Soar consists of both software and hardware components carefully designed to overcome various system and physical challenges. Soar can leverage the existing operational infrastructure like street lampposts for a lower barrier of adoption. Soar adopts a new communication architecture that comprises a bi-directional multi-hop I2I network and a downlink I2V broadcast service, which are designed based on off-the-shelf 802.11ac interfaces in an integrated manner. Soar also features a hierarchical DL task management framework to achieve desirable load balancing among nodes and enable them to collaborate efficiently to run multiple data-intensive autonomous driving applications. We deployed a total of 18 Soar nodes on existing lampposts on campus, which have been operational for over two years. Our real-world evaluation shows that Soar can support a diverse set of autonomous driving applications and achieve desirable real-time performance and high communication reliability. Our findings and experiences in this work offer key insights into the development and deployment of next-generation smart roadside infrastructure and autonomous driving systems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_13786 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Soar: Design and Deployment of A Smart Roadside Infrastructure System for Autonomous Driving Shi, Shuyao Ling, Neiwen Jiang, Zhehao Huang, Xuan He, Yuze Zhao, Xiaoguang Yang, Bufang Bian, Chen Xia, Jingfei Yan, Zhenyu Yeung, Raymond Xing, Guoliang Systems and Control Artificial Intelligence Distributed, Parallel, and Cluster Computing Machine Learning Recently,smart roadside infrastructure (SRI) has demonstrated the potential of achieving fully autonomous driving systems. To explore the potential of infrastructure-assisted autonomous driving, this paper presents the design and deployment of Soar, the first end-to-end SRI system specifically designed to support autonomous driving systems. Soar consists of both software and hardware components carefully designed to overcome various system and physical challenges. Soar can leverage the existing operational infrastructure like street lampposts for a lower barrier of adoption. Soar adopts a new communication architecture that comprises a bi-directional multi-hop I2I network and a downlink I2V broadcast service, which are designed based on off-the-shelf 802.11ac interfaces in an integrated manner. Soar also features a hierarchical DL task management framework to achieve desirable load balancing among nodes and enable them to collaborate efficiently to run multiple data-intensive autonomous driving applications. We deployed a total of 18 Soar nodes on existing lampposts on campus, which have been operational for over two years. Our real-world evaluation shows that Soar can support a diverse set of autonomous driving applications and achieve desirable real-time performance and high communication reliability. Our findings and experiences in this work offer key insights into the development and deployment of next-generation smart roadside infrastructure and autonomous driving systems. |
| title | Soar: Design and Deployment of A Smart Roadside Infrastructure System for Autonomous Driving |
| topic | Systems and Control Artificial Intelligence Distributed, Parallel, and Cluster Computing Machine Learning |
| url | https://arxiv.org/abs/2404.13786 |