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Development of a Framework for Generating Driving Safety Assessment Scenarios for Automated Vehicles
Despite the technological advances in automated driving systems, traffic accidents involving automated vehicles (AVs) continue to occur, raising concerns over the safety and reliability of automated driving. For the smooth commercialization of AVs, it is necessary to systematically assess the drivin...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9412556/ https://www.ncbi.nlm.nih.gov/pubmed/36015798 http://dx.doi.org/10.3390/s22166031 |
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author | Ko, Woori Park, Sangmin Yun, Jaewoong Park, Sungho Yun, Ilsoo |
author_facet | Ko, Woori Park, Sangmin Yun, Jaewoong Park, Sungho Yun, Ilsoo |
author_sort | Ko, Woori |
collection | PubMed |
description | Despite the technological advances in automated driving systems, traffic accidents involving automated vehicles (AVs) continue to occur, raising concerns over the safety and reliability of automated driving. For the smooth commercialization of AVs, it is necessary to systematically assess the driving safety of AVs under the various situations that they potentially face. In this context, these various situations are mostly implemented by using systematically developed scenarios. In accordance with this need, a scenario generation framework for the assessment of the driving safety of AVs is proposed by this study. The proposed framework provides a unified form of assessment with key components for each scenario stage to facilitate systematization and objectivity. The performance of the driving safety assessment scenarios generated within the proposed framework was verified. Traffic accident report data were used for verification, and the usefulness of the proposed framework was confirmed by generating a set of scenarios, ranging from functional scenarios to test cases. The scenario generation framework proposed in this study can be used to provide sustainable scenarios. In addition, from this, it is possible to create assessment scenarios for all road types and various assessment spaces, such as simulations, proving grounds, and real roads. |
format | Online Article Text |
id | pubmed-9412556 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-94125562022-08-27 Development of a Framework for Generating Driving Safety Assessment Scenarios for Automated Vehicles Ko, Woori Park, Sangmin Yun, Jaewoong Park, Sungho Yun, Ilsoo Sensors (Basel) Article Despite the technological advances in automated driving systems, traffic accidents involving automated vehicles (AVs) continue to occur, raising concerns over the safety and reliability of automated driving. For the smooth commercialization of AVs, it is necessary to systematically assess the driving safety of AVs under the various situations that they potentially face. In this context, these various situations are mostly implemented by using systematically developed scenarios. In accordance with this need, a scenario generation framework for the assessment of the driving safety of AVs is proposed by this study. The proposed framework provides a unified form of assessment with key components for each scenario stage to facilitate systematization and objectivity. The performance of the driving safety assessment scenarios generated within the proposed framework was verified. Traffic accident report data were used for verification, and the usefulness of the proposed framework was confirmed by generating a set of scenarios, ranging from functional scenarios to test cases. The scenario generation framework proposed in this study can be used to provide sustainable scenarios. In addition, from this, it is possible to create assessment scenarios for all road types and various assessment spaces, such as simulations, proving grounds, and real roads. MDPI 2022-08-12 /pmc/articles/PMC9412556/ /pubmed/36015798 http://dx.doi.org/10.3390/s22166031 Text en © 2022 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 Ko, Woori Park, Sangmin Yun, Jaewoong Park, Sungho Yun, Ilsoo Development of a Framework for Generating Driving Safety Assessment Scenarios for Automated Vehicles |
title | Development of a Framework for Generating Driving Safety Assessment Scenarios for Automated Vehicles |
title_full | Development of a Framework for Generating Driving Safety Assessment Scenarios for Automated Vehicles |
title_fullStr | Development of a Framework for Generating Driving Safety Assessment Scenarios for Automated Vehicles |
title_full_unstemmed | Development of a Framework for Generating Driving Safety Assessment Scenarios for Automated Vehicles |
title_short | Development of a Framework for Generating Driving Safety Assessment Scenarios for Automated Vehicles |
title_sort | development of a framework for generating driving safety assessment scenarios for automated vehicles |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9412556/ https://www.ncbi.nlm.nih.gov/pubmed/36015798 http://dx.doi.org/10.3390/s22166031 |
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