Leveraging the GIDAS Database for the Criticality Analysis of Automated Driving Systems
A safe introduction of automated driving systems on urban roads requires a thorough understanding of the traffic conflicts and accidents. This understanding is paramount to constructively safeguard these systems, i.e., to design a system that exhibits an adequate performance even in critical situati...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2023-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2023/1349269 |
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| _version_ | 1850234833811275776 |
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| author | Stefan Babisch Christian Neurohr Lukas Westhofen Stefan Schoenawa Henrik Liers |
| author_facet | Stefan Babisch Christian Neurohr Lukas Westhofen Stefan Schoenawa Henrik Liers |
| author_sort | Stefan Babisch |
| collection | DOAJ |
| description | A safe introduction of automated driving systems on urban roads requires a thorough understanding of the traffic conflicts and accidents. This understanding is paramount to constructively safeguard these systems, i.e., to design a system that exhibits an adequate performance even in critical situations. In this work, we present an approach to gather knowledge by analyzing the German In-Depth Accident Study (GIDAS) database, which is representative of all German traffic accidents, along with the influencing factors that are hypothesized to be associated with increased criticality in relation to automated driving. In order to gain an insight into the risk associated with these factors in real-world accidents, we determine their presence in the database’s accident cases within a selected operational domain, enabled by translation from a natural language description to the database scheme employed by GIDAS. This initial catalog as well as the subsequent statistical considerations is motivated by analyzing the criticality for automated driving systems in urban areas. Based on this catalog, our work delineates a method for quantification of risk associated with such influencing factors in a given operational domain based on real-world accident data. This quantification can subsequently be used in decompositional, scenario-based risk assessment before system design and for the embedding safety argumentation. This paper, therefore, provides a blueprint of how the matured field of traffic accident research studies and its results, in particular accident databases, can be leveraged for risk assessment of the operational domain of automated driving systems. |
| format | Article |
| id | doaj-art-0f8ca68dc62c4b388dbbf1b9a1fa5cc8 |
| institution | OA Journals |
| issn | 2042-3195 |
| language | English |
| publishDate | 2023-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-0f8ca68dc62c4b388dbbf1b9a1fa5cc82025-08-20T02:02:30ZengWileyJournal of Advanced Transportation2042-31952023-01-01202310.1155/2023/1349269Leveraging the GIDAS Database for the Criticality Analysis of Automated Driving SystemsStefan Babisch0Christian Neurohr1Lukas Westhofen2Stefan Schoenawa3Henrik Liers4VUFO GmbHGerman Aerospace Center (DLR) e.V.German Aerospace Center (DLR) e.V.Volkswagen GroupVUFO GmbHA safe introduction of automated driving systems on urban roads requires a thorough understanding of the traffic conflicts and accidents. This understanding is paramount to constructively safeguard these systems, i.e., to design a system that exhibits an adequate performance even in critical situations. In this work, we present an approach to gather knowledge by analyzing the German In-Depth Accident Study (GIDAS) database, which is representative of all German traffic accidents, along with the influencing factors that are hypothesized to be associated with increased criticality in relation to automated driving. In order to gain an insight into the risk associated with these factors in real-world accidents, we determine their presence in the database’s accident cases within a selected operational domain, enabled by translation from a natural language description to the database scheme employed by GIDAS. This initial catalog as well as the subsequent statistical considerations is motivated by analyzing the criticality for automated driving systems in urban areas. Based on this catalog, our work delineates a method for quantification of risk associated with such influencing factors in a given operational domain based on real-world accident data. This quantification can subsequently be used in decompositional, scenario-based risk assessment before system design and for the embedding safety argumentation. This paper, therefore, provides a blueprint of how the matured field of traffic accident research studies and its results, in particular accident databases, can be leveraged for risk assessment of the operational domain of automated driving systems.http://dx.doi.org/10.1155/2023/1349269 |
| spellingShingle | Stefan Babisch Christian Neurohr Lukas Westhofen Stefan Schoenawa Henrik Liers Leveraging the GIDAS Database for the Criticality Analysis of Automated Driving Systems Journal of Advanced Transportation |
| title | Leveraging the GIDAS Database for the Criticality Analysis of Automated Driving Systems |
| title_full | Leveraging the GIDAS Database for the Criticality Analysis of Automated Driving Systems |
| title_fullStr | Leveraging the GIDAS Database for the Criticality Analysis of Automated Driving Systems |
| title_full_unstemmed | Leveraging the GIDAS Database for the Criticality Analysis of Automated Driving Systems |
| title_short | Leveraging the GIDAS Database for the Criticality Analysis of Automated Driving Systems |
| title_sort | leveraging the gidas database for the criticality analysis of automated driving systems |
| url | http://dx.doi.org/10.1155/2023/1349269 |
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