自動運転のためのスマートモビリティデジタルツイン:設計と概念実証
Smart Mobility Digital Twin for Automated Driving: Design and Proof-of-Concept
センシングとクラウド/エッジコンピューティングを活用し、実世界の静的・動的物体をリアルタイムに反映するデジタルツインを構築して、協調環境認識による交通監視と経路計画を実現し、実車による概念実証で機能と遅延性能を検証した。
著者: Kui Wang, Zongdian Li, Tao Yu, Kei Sakaguchi
分類: cs.RO, cs.SY, eess.SY
原文アブストラクト
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.
関連論文
- クエリ駆動型通信効率の高い自動運転向けデジタルツイン設計自動運転/デジタルツイン
- 学習型自動運転車の交通標識認識に向けたデジタルツイン試作自動運転/デジタルツイン
