TU Darmstadt / ULB / TUprints

Fundamental Design Criteria for Logical Scenarios in Simulation-based Safety Validation of Automated Driving Using Sensor Model Knowledge

Elster, Lukas ; Linnhoff, Clemens ; Rosenberger, Philipp ; Schmidt, Simon ; Stark, Rainer ; Winner, Hermann (2021)
Fundamental Design Criteria for Logical Scenarios in Simulation-based Safety Validation of Automated Driving Using Sensor Model Knowledge.
IV Workshop on Ensuring and Validating Safety for Automated Vehicles. Nagoya (11.07.2021-11.07.2021)
doi: 10.26083/tuprints-00018950
Conference or Workshop Item, Secondary publication, Postprint

[img]
Preview
Text
2021_IV_WS.pdf
Copyright Information: In Copyright.

Download (258kB) | Preview
Item Type: Conference or Workshop Item
Type of entry: Secondary publication
Title: Fundamental Design Criteria for Logical Scenarios in Simulation-based Safety Validation of Automated Driving Using Sensor Model Knowledge
Language: English
Date: 2021
Place of Publication: Darmstadt
Year of primary publication: 2021
Collation: 6 ungezählte Seiten
Event Title: IV Workshop on Ensuring and Validating Safety for Automated Vehicles
Event Location: Nagoya
Event Dates: 11.07.2021-11.07.2021
DOI: 10.26083/tuprints-00018950
Origin: Secondary publication
Abstract:

Scenario-based virtual validation of automated driving functions is a promising method to reduce testing effort in real traffic. In this work, a method for deriving scenario design criteria from a sensor modeling point of view is proposed. Using basic sensor technology specific equations as rough but effective boundary conditions, the accessible information for the system under test are determined. Subsequently, initial conditions such as initial poses of dynamic objects are calculated using the derived boundary conditions for designing logical scenarios. Further interest is given on triggers starting movements of objects during scenarios that are not time but object dependent. The approach is demonstrated on the example of the radar equation and first exemplary results by identifying relevance regions are shown.

Status: Postprint
URN: urn:nbn:de:tuda-tuprints-189501
Classification DDC: 600 Technology, medicine, applied sciences > 620 Engineering and machine engineering
Divisions: 16 Department of Mechanical Engineering > Institute of Automotive Engineering (FZD)
TU-Projects: TÜV Rheinland|19A19004E|SETLevel4to5
Bund/BMWi|19A19002S|VVMethoden
Date Deposited: 09 Jul 2021 06:45
Last Modified: 22 Jun 2023 13:32
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/18950
PPN: 48325276X
Export:
Actions (login required)
View Item View Item