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Configurable Sensor Model Architecture for the Development of Automated Driving Systems

Sensor models provide the required environmental perception information for the development and testing of automated driving systems in virtual vehicle environments. In this article, a configurable sensor model architecture is introduced. Based on methods of model-based systems engineering (MBSE) an...

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Detalles Bibliográficos
Autores principales: Schmidt, Simon, Schlager, Birgit, Muckenhuber, Stefan, Stark, Rainer
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8309557/
https://www.ncbi.nlm.nih.gov/pubmed/34300426
http://dx.doi.org/10.3390/s21144687
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author Schmidt, Simon
Schlager, Birgit
Muckenhuber, Stefan
Stark, Rainer
author_facet Schmidt, Simon
Schlager, Birgit
Muckenhuber, Stefan
Stark, Rainer
author_sort Schmidt, Simon
collection PubMed
description Sensor models provide the required environmental perception information for the development and testing of automated driving systems in virtual vehicle environments. In this article, a configurable sensor model architecture is introduced. Based on methods of model-based systems engineering (MBSE) and functional decomposition, this approach supports a flexible and continuous way to use sensor models in automotive development. Modeled sensor effects, representing single-sensor properties, are combined to an overall sensor behavior. This improves reusability and enables adaptation to specific requirements of the development. Finally, a first practical application of the configurable sensor model architecture is demonstrated, using two exemplary sensor effects: the geometric field of view (FoV) and the object-dependent FoV.
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spelling pubmed-83095572021-07-25 Configurable Sensor Model Architecture for the Development of Automated Driving Systems Schmidt, Simon Schlager, Birgit Muckenhuber, Stefan Stark, Rainer Sensors (Basel) Article Sensor models provide the required environmental perception information for the development and testing of automated driving systems in virtual vehicle environments. In this article, a configurable sensor model architecture is introduced. Based on methods of model-based systems engineering (MBSE) and functional decomposition, this approach supports a flexible and continuous way to use sensor models in automotive development. Modeled sensor effects, representing single-sensor properties, are combined to an overall sensor behavior. This improves reusability and enables adaptation to specific requirements of the development. Finally, a first practical application of the configurable sensor model architecture is demonstrated, using two exemplary sensor effects: the geometric field of view (FoV) and the object-dependent FoV. MDPI 2021-07-08 /pmc/articles/PMC8309557/ /pubmed/34300426 http://dx.doi.org/10.3390/s21144687 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Schmidt, Simon
Schlager, Birgit
Muckenhuber, Stefan
Stark, Rainer
Configurable Sensor Model Architecture for the Development of Automated Driving Systems
title Configurable Sensor Model Architecture for the Development of Automated Driving Systems
title_full Configurable Sensor Model Architecture for the Development of Automated Driving Systems
title_fullStr Configurable Sensor Model Architecture for the Development of Automated Driving Systems
title_full_unstemmed Configurable Sensor Model Architecture for the Development of Automated Driving Systems
title_short Configurable Sensor Model Architecture for the Development of Automated Driving Systems
title_sort configurable sensor model architecture for the development of automated driving systems
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8309557/
https://www.ncbi.nlm.nih.gov/pubmed/34300426
http://dx.doi.org/10.3390/s21144687
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