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Bibliographic Details
Main Authors: Graubohm, Robert, Stolte, Torben, Bagschik, Gerrit, Maurer, Markus
Format: Preprint
Published: 2020
Subjects:
Online Access:https://arxiv.org/abs/2004.10501
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author Graubohm, Robert
Stolte, Torben
Bagschik, Gerrit
Maurer, Markus
author_facet Graubohm, Robert
Stolte, Torben
Bagschik, Gerrit
Maurer, Markus
contents The complex functional structure of driverless vehicles induces a multitude of potential malfunctions. Established approaches for a systematic hazard identification generate individual potentially hazardous scenarios for each identified malfunction. This leads to inefficiencies in a purely expert-based hazard analysis process, as each of the many scenarios has to be examined individually. In this contribution, we propose an adaptation of the strategy for hazard identification for the development of automated vehicles. Instead of focusing on malfunctions, we base our process on deviations from desired vehicle behavior in selected operational scenarios analyzed in the concept phase. By evaluating externally observable deviations from a desired behavior, we encapsulate individual malfunctions and reduce the amount of generated potentially hazardous scenarios. After introducing our hazard identification strategy, we illustrate its application on one of the operational scenarios used in the research project UNICAR$agil$.
format Preprint
id arxiv_https___arxiv_org_abs_2004_10501
institution arXiv
publishDate 2020
record_format arxiv
spellingShingle Towards Efficient Hazard Identification in the Concept Phase of Driverless Vehicle Development
Graubohm, Robert
Stolte, Torben
Bagschik, Gerrit
Maurer, Markus
Systems and Control
The complex functional structure of driverless vehicles induces a multitude of potential malfunctions. Established approaches for a systematic hazard identification generate individual potentially hazardous scenarios for each identified malfunction. This leads to inefficiencies in a purely expert-based hazard analysis process, as each of the many scenarios has to be examined individually. In this contribution, we propose an adaptation of the strategy for hazard identification for the development of automated vehicles. Instead of focusing on malfunctions, we base our process on deviations from desired vehicle behavior in selected operational scenarios analyzed in the concept phase. By evaluating externally observable deviations from a desired behavior, we encapsulate individual malfunctions and reduce the amount of generated potentially hazardous scenarios. After introducing our hazard identification strategy, we illustrate its application on one of the operational scenarios used in the research project UNICAR$agil$.
title Towards Efficient Hazard Identification in the Concept Phase of Driverless Vehicle Development
topic Systems and Control
url https://arxiv.org/abs/2004.10501