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Predicting takeover response to silent automated vehicle failures
Current and foreseeable automated vehicles are not able to respond appropriately in all circumstances and require human monitoring. An experimental examination of steering automation failure shows that response latency, variability and corrective manoeuvring systematically depend on failure severity...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7703974/ https://www.ncbi.nlm.nih.gov/pubmed/33253219 http://dx.doi.org/10.1371/journal.pone.0242825 |
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author | Mole, Callum Pekkanen, Jami Sheppard, William Louw, Tyron Romano, Richard Merat, Natasha Markkula, Gustav Wilkie, Richard |
author_facet | Mole, Callum Pekkanen, Jami Sheppard, William Louw, Tyron Romano, Richard Merat, Natasha Markkula, Gustav Wilkie, Richard |
author_sort | Mole, Callum |
collection | PubMed |
description | Current and foreseeable automated vehicles are not able to respond appropriately in all circumstances and require human monitoring. An experimental examination of steering automation failure shows that response latency, variability and corrective manoeuvring systematically depend on failure severity and the cognitive load of the driver. The results are formalised into a probabilistic predictive model of response latencies that accounts for failure severity, cognitive load and variability within and between drivers. The model predicts high rates of unsafe outcomes in plausible automation failure scenarios. These findings underline that understanding variability in failure responses is crucial for understanding outcomes in automation failures. |
format | Online Article Text |
id | pubmed-7703974 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-77039742020-12-03 Predicting takeover response to silent automated vehicle failures Mole, Callum Pekkanen, Jami Sheppard, William Louw, Tyron Romano, Richard Merat, Natasha Markkula, Gustav Wilkie, Richard PLoS One Research Article Current and foreseeable automated vehicles are not able to respond appropriately in all circumstances and require human monitoring. An experimental examination of steering automation failure shows that response latency, variability and corrective manoeuvring systematically depend on failure severity and the cognitive load of the driver. The results are formalised into a probabilistic predictive model of response latencies that accounts for failure severity, cognitive load and variability within and between drivers. The model predicts high rates of unsafe outcomes in plausible automation failure scenarios. These findings underline that understanding variability in failure responses is crucial for understanding outcomes in automation failures. Public Library of Science 2020-11-30 /pmc/articles/PMC7703974/ /pubmed/33253219 http://dx.doi.org/10.1371/journal.pone.0242825 Text en © 2020 Mole et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Mole, Callum Pekkanen, Jami Sheppard, William Louw, Tyron Romano, Richard Merat, Natasha Markkula, Gustav Wilkie, Richard Predicting takeover response to silent automated vehicle failures |
title | Predicting takeover response to silent automated vehicle failures |
title_full | Predicting takeover response to silent automated vehicle failures |
title_fullStr | Predicting takeover response to silent automated vehicle failures |
title_full_unstemmed | Predicting takeover response to silent automated vehicle failures |
title_short | Predicting takeover response to silent automated vehicle failures |
title_sort | predicting takeover response to silent automated vehicle failures |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7703974/ https://www.ncbi.nlm.nih.gov/pubmed/33253219 http://dx.doi.org/10.1371/journal.pone.0242825 |
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