Geotagged Visual Localisation System for Urban Automated Vehicles
- 提供方法
- 版元よりダウンロードリンクを連絡
- 形態
- 価格
- 一般価格(税込)：￥6,600 会員価格(税込)：￥5,280
- 文献・情報種別
- SAE Paper
No.2022-01-0098
- 掲載ページ
- 1-13(Total 13 p)
- 発行年月
- 2022年 3月
- 出版社
- SAE International
- 言語
- 英語
- イベント
- WCX SAE World Congress Experience 2022
書誌事項
| 著者（英） | 1) Alireza Ahrabian, 2) Ioannis Souflas, 3) Noyan Songur, 4) Erik Nielsen, 5) Caroline Broughton, 6) Chris Holmes |
|---|---|
| 勤務先（英） | 1) Hitachi Europe Limited, 2) Hitachi Europe Limited, 3) Hitachi Europe Limited, 4) Connected Places Catapult, 5) Connected Places Catapult, 6) Nissan Motor Manufacturing Ltd. |
| 抄録（英） | Vehicle localisation is one of the fundamental building blocks of automated driving systems. Although, high-end satellite navigation systems can provide centimetre-level accuracy, they are limited to applications where there is sufficient satellite signal visibility. One example where signals from navigational satellites might deteriorate is urban canyons which are characterised by high rise, high density residential and commercial buildings. To overcome the limitations of satellite navigation systems, most state-of-the-art localisation solutions fuse information from multiple sensors such as GNSS, LiDAR, camera, accelerometer, and wheel encoder with the purpose of creating a full 3D map of the operating environment. Although this approach provides accurate and reliable results, it is bounded in terms of data efficiency and scalability. With these limitations in mind an alternative methodology is proposed. More specifically, as opposed to existing approaches, the proposed system eliminates the need for creating full 3D maps by activating a visual localisation system only in geographical areas where the accuracy of satellite navigation systems might deteriorate, particularly urban canyons. The existence of urban canyons is pre-determined depending on the visibility of sky which is calculated using a digital surface model (DSM) of the environment. As a result, 3D maps are created only in challenging GNSS denied areas which makes the overall localisation and map systems much lighter improving the data efficiency and scalability. The paper will be covering the technical details of the proposed solution and will be showing the efficacy of the approach with results obtained in real-world urban environments. 翻訳 |
