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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. (Postprint)
In: 24th International Conference on Intelligent Transportation Systems (ITSC),
Darmstadt, IEEE, 24th International Conference on Intelligent Transportation Systems (ITSC), Indianapolis, IN, USA, 19.-22.09.2021, DOI: 10.26083/tuprints-00018949,
[Conference or Workshop Item]

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.

Item Type: Conference or Workshop Item
Erschienen: 2021
Creators: Linnhoff, Clemens ; Rosenberger, Philipp ; Schmidt, Simon ; Elster, Lukas ; Stark, Rainer ; Winner, Hermann
Status: Postprint
Title: Towards Serious Perception Sensor Simulation for Safety Validation of Automated Driving - A Collaborative Method to Specify Sensor Models
Language: English
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.

Title of Book: 24th International Conference on Intelligent Transportation Systems (ITSC)
Place of Publication: Darmstadt
Publisher: IEEE
Collation: 8 Seiten
Divisions: 16 Department of Mechanical Engineering
16 Department of Mechanical Engineering > Institute of Automotive Engineering (FZD)
16 Department of Mechanical Engineering > Institute of Automotive Engineering (FZD) > Driver Assistance
TU-Projects: TÜV Rheinland|19A19004E|SETLevel4to5
Bund/BMWi|19A19002S|VVMethoden
Event Title: 24th International Conference on Intelligent Transportation Systems (ITSC)
Event Location: Indianapolis, IN, USA
Event Dates: 19.-22.09.2021
Date Deposited: 02 Jul 2021 12:09
DOI: 10.26083/tuprints-00018949
Official URL: https://tuprints.ulb.tu-darmstadt.de/18949
URN: urn:nbn:de:tuda-tuprints-189491
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