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Highly Parameterizable and Generic Perception Sensor Model Architecture

Linnhoff, Clemens ; Rosenberger, Philipp ; Holder, Martin Friedrich ; Cianciaruso, Nicodemo ; Winner, Hermann (2021)
Highly Parameterizable and Generic Perception Sensor Model Architecture.
6th International ATZ Conference Automated Driving. Wiesbaden (13.10. - 14.10.2020)
doi: 10.26083/tuprints-00018672
Conference or Workshop Item, Secondary publication, Postprint

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Item Type: Conference or Workshop Item
Type of entry: Secondary publication
Title: Highly Parameterizable and Generic Perception Sensor Model Architecture
Language: German
Date: 2021
Place of Publication: Darmstadt
Year of primary publication: 2020
Publisher: Springer Vieweg
Book Title: Automatisiertes Fahren 2020 - Von der Fahrerassistenz zum autonomen Fahren - 6. Internationale ATZ-Fachtagung
Collation: 12 Seiten
Event Title: 6th International ATZ Conference Automated Driving
Event Location: Wiesbaden
Event Dates: 13.10. - 14.10.2020
DOI: 10.26083/tuprints-00018672
Origin: Secondary publication
Abstract:

Scenario-based virtual testing is seen as a key element to bring the overall safety validation effort for automated driving functions to an economically feasible level. In this work, a generic and modular architecture for simulation of automotive perception sensors is introduced, as part of the overall virtual testing pipeline. It is based on the functional decomposition of real world perception sensors. All interfaces between the individual modules of the model architecture are oriented on internationally recognized standards and therefore facilitate a high degree of interchangeability. In addition, a wrapper framework handles all outer communication and enables a profile-based parameterization of the model, where every profile reflects a specific set of parameters tailored to the specifications and use case of the end user.

Status: Postprint
URN: urn:nbn:de:tuda-tuprints-186725
Classification DDC: 600 Technology, medicine, applied sciences > 620 Engineering and machine engineering
Divisions: 16 Department of Mechanical Engineering > Institute of Automotive Engineering (FZD) > Driver Assistance
TU-Projects: TÜV Rheinland|19A19004E|SETLevel4to5
Bund/BMWi|19A19002S|VVMethoden
Date Deposited: 13 Jul 2021 10:38
Last Modified: 16 Nov 2021 12:07
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/18672
PPN: 481608052
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