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• W3108045986 startingPage "e0242825" @default.
• W3108045986 abstract "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." @default.
• W3108045986 created "2020-12-07" @default.
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• W3108045986 date "2020-11-30" @default.
• W3108045986 modified "2023-10-17" @default.
• W3108045986 title "Predicting takeover response to silent automated vehicle failures" @default.
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• W3108045986 doi "https://doi.org/10.1371/journal.pone.0242825" @default.
• W3108045986 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/7703974" @default.
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• W3108045986 hasPublicationYear "2020" @default.
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