| Project/Area Number |
15F15047
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| Research Category |
Grant-in-Aid for JSPS Fellows
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| Allocation Type | Single-year Grants |
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| Section | 外国 |
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| Research Field |
Perceptual information processing
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| Research Institution | The University of Tokyo |
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Principal Investigator |
上條 俊介 東京大学, 大学院情報学環・学際情報学府, 准教授 (70334357)
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| Co-Investigator(Kenkyū-buntansha) |
HSU LI-TA 東京大学, 大学院情報学環・学際情報学府, 外国人特別研究員
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| Project Period (FY) |
2015-04-24 – 2017-03-31
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| Project Status |
Completed (Fiscal Year 2016)
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| Budget Amount *help |
¥2,300,000 (Direct Cost: ¥2,300,000)
Fiscal Year 2016: ¥1,100,000 (Direct Cost: ¥1,100,000)
Fiscal Year 2015: ¥1,200,000 (Direct Cost: ¥1,200,000)
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| Keywords | GPS / GNSS / Multipath / Urban canyon / Localization / 3D Map / 3D maps / 3D building model / Urban Canyon / RAIM / Autonomous driving |
|---|
| Outline of Annual Research Achievements |
Precise positioning is essential to realize autonomous driving in city urban area. The common understanding is GNSS receiver, LiDAR and vision sensor are integrated to provide localization service with lane-level accuracy. In general, the width of lane is about 3 meters. According to recent studies, localization methods of GNSS, LiDAR and camera can be improved by applying 2D maps and 3D models. Since 2007, using 3D building models as aids to mitigate/exclude/correct the multipath and non-line-of-sight effects has become a popular approach to enhance GNSS receivers. We propose an innovative GPS error correction method by the use of 3D building model and ray-tracing simulation. Finally, the proposed method successfully achieves a performance with less than 3 meters of positioning error.
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| Research Progress Status |
28年度が最終年度であるため、記入しない。
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| Strategy for Future Research Activity |
28年度が最終年度であるため、記入しない。
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