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Towards Serious Perception Sensor Simulation for Safety Validation of Automated Driving - A Collaborative Method to Specify Sensor Models

Linnhoff, Clemens ; Rosenberger, Philipp ; Schmidt, Simon ; Elster, Lukas ; Stark, Rainer ; Winner, Hermann (2021)
Towards Serious Perception Sensor Simulation for Safety Validation of Automated Driving - A Collaborative Method to Specify Sensor Models.
24th International Conference on Intelligent Transportation Systems (ITSC). Indianapolis, IN, USA (19.-22.09.2021)
doi: 10.26083/tuprints-00018949
Konferenzveröffentlichung, Erstveröffentlichung, Postprint

Kurzbeschreibung (Abstract)

Perception sensor modeling is essential for the safety validation of automated driving systems in virtual environments. Nevertheless, the community lacks a methodical approach to derive requirements for such sensor models that enables a serious application for safety validation in the first place. This article provides a method to specify sensor models for the environmental perception of automated driving systems. The key of the approach is a collaborative collection of cause-effect chains as the basis for specification. With this collection at hand, a tabular form is introduced to extract the relevance of the effect chains to be modeled. Combined profound expert assessments in the table enable the test engineer to specify sensor models within a traceable decision-making process.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2021
Autor(en): Linnhoff, Clemens ; Rosenberger, Philipp ; Schmidt, Simon ; Elster, Lukas ; Stark, Rainer ; Winner, Hermann
Art des Eintrags: Erstveröffentlichung
Titel: Towards Serious Perception Sensor Simulation for Safety Validation of Automated Driving - A Collaborative Method to Specify Sensor Models
Sprache: Englisch
Publikationsjahr: 2021
Ort: Darmstadt
Verlag: IEEE
Buchtitel: 24th International Conference on Intelligent Transportation Systems (ITSC)
Kollation: 8 Seiten
Veranstaltungstitel: 24th International Conference on Intelligent Transportation Systems (ITSC)
Veranstaltungsort: Indianapolis, IN, USA
Veranstaltungsdatum: 19.-22.09.2021
DOI: 10.26083/tuprints-00018949
URL / URN: https://tuprints.ulb.tu-darmstadt.de/18949
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Kurzbeschreibung (Abstract):

Perception sensor modeling is essential for the safety validation of automated driving systems in virtual environments. Nevertheless, the community lacks a methodical approach to derive requirements for such sensor models that enables a serious application for safety validation in the first place. This article provides a method to specify sensor models for the environmental perception of automated driving systems. The key of the approach is a collaborative collection of cause-effect chains as the basis for specification. With this collection at hand, a tabular form is introduced to extract the relevance of the effect chains to be modeled. Combined profound expert assessments in the table enable the test engineer to specify sensor models within a traceable decision-making process.

Status: Postprint
URN: urn:nbn:de:tuda-tuprints-189491
Sachgruppe der Dewey Dezimalklassifikatin (DDC): 600 Technik, Medizin, angewandte Wissenschaften > 620 Ingenieurwissenschaften und Maschinenbau
Fachbereich(e)/-gebiet(e): 16 Fachbereich Maschinenbau
16 Fachbereich Maschinenbau > Fachgebiet Fahrzeugtechnik (FZD)
16 Fachbereich Maschinenbau > Fachgebiet Fahrzeugtechnik (FZD) > Fahrerassistenzssysteme
TU-Projekte: TÜV Rheinland|19A19004E|SETLevel4to5
Bund/BMWi|19A19002S|VVMethoden
Hinterlegungsdatum: 02 Jul 2021 12:09
Letzte Änderung: 16 Nov 2021 12:23
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