Smart Mobility Digital Twin for Automated Driving: Design and Proof-of-Concept
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arXiv
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| Hauptverfasser: | , , , |
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| Format: | Preprint |
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2023
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| _version_ | 1866916094215716864 |
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| author | Wang, Kui Li, Zongdian Yu, Tao Sakaguchi, Kei |
| author_facet | Wang, Kui Li, Zongdian Yu, Tao Sakaguchi, Kei |
| contents | During the past decade, smart mobility and intelligent vehicles have attracted increasing attention, because they promise to create a highly efficient and safe transportation system in the future. Meanwhile, digital twin, as an emerging technology, will play an important role in automated driving and intelligent transportation systems. This technology is applied in this paper to design a platform for smart mobility, providing large-scale route planning services. Utilizing sensing technologies and cloud/edge computing, we build a digital twin system model that reflects the static and dynamic objects from the real world in real time. With the smart mobility platform, we realize traffic monitoring and route planning through cooperative environment perception to help automated vehicles circumvent jams. A proof-of-concept test with a real vehicle in real traffic is conducted to validate the functions and the delay performance of the proposed platform. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_08654 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Smart Mobility Digital Twin for Automated Driving: Design and Proof-of-Concept Wang, Kui Li, Zongdian Yu, Tao Sakaguchi, Kei Robotics Systems and Control During the past decade, smart mobility and intelligent vehicles have attracted increasing attention, because they promise to create a highly efficient and safe transportation system in the future. Meanwhile, digital twin, as an emerging technology, will play an important role in automated driving and intelligent transportation systems. This technology is applied in this paper to design a platform for smart mobility, providing large-scale route planning services. Utilizing sensing technologies and cloud/edge computing, we build a digital twin system model that reflects the static and dynamic objects from the real world in real time. With the smart mobility platform, we realize traffic monitoring and route planning through cooperative environment perception to help automated vehicles circumvent jams. A proof-of-concept test with a real vehicle in real traffic is conducted to validate the functions and the delay performance of the proposed platform. |
| title | Smart Mobility Digital Twin for Automated Driving: Design and Proof-of-Concept |
| topic | Robotics Systems and Control |
| url | https://arxiv.org/abs/2401.08654 |