2021 Kleinheubach Conference 2021
DOI: 10.23919/ieeeconf54431.2021.9598409
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Cooperative RADAR Sensors for the Digital Test Field A9 (KoRA9) – Algorithmic Recap and Lessons Learned

Abstract: Infrastructure sensing systems in combination with Infrastructure-to-Vehicle communication can be used to enhance sensor data obtained from the perspective of a vehicle, only. This paper presents a system consisting of a radar sensor network installed at the side of the street, together with an Edge Processing Unit to fuse the data of different sensors. Measurements taken by the demonstrator are shown, the system architecture is discussed, and some lessons learned are presented.

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Cited by 3 publications
(1 citation statement)
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“…Such sensor setups have an elevated view angle, which reduces on-road occlusion to a large extent compared with vehicle-based perception [16], [17]. However, in presently available infrastructure-based setups, as described in Table III of [18], projects like [19]- [21] (only some are cited for reference) have used 2D radar sensors along with cameras and/or lidar, but 3D radar sensor that can provide enhanced perception has not yet been explored. To close this gap, the proposed work uses a smart infrastructure-based setup, as described in [17] for the proposed semi-automatic annotation methodology.…”
Section: Introductionmentioning
confidence: 99%
“…Such sensor setups have an elevated view angle, which reduces on-road occlusion to a large extent compared with vehicle-based perception [16], [17]. However, in presently available infrastructure-based setups, as described in Table III of [18], projects like [19]- [21] (only some are cited for reference) have used 2D radar sensors along with cameras and/or lidar, but 3D radar sensor that can provide enhanced perception has not yet been explored. To close this gap, the proposed work uses a smart infrastructure-based setup, as described in [17] for the proposed semi-automatic annotation methodology.…”
Section: Introductionmentioning
confidence: 99%