Evidence map›Paper›PMID 33253219›Full record

ArticlePloS one2020

Predicting takeover response to silent automated vehicle failures.

Callum Mole, Jami Pekkanen, William Sheppard, Tyron Louw, Richard Romano, Natasha Merat, Gustav Markkula, Richard Wilkie

Abstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Callum MoleSchool of Psychology, University of Leeds, Leeds, United Kingdom.ORCID 0000-0002-1463-6419
Jami PekkanenSchool of Psychology, University of Leeds, Leeds, United Kingdom.
William SheppardSchool of Psychology, University of Leeds, Leeds, United Kingdom.ORCID 0000-0002-2691-6469
Tyron LouwInstitute of Transport Studies, University of Leeds, Leeds, United Kingdom.ORCID 0000-0001-6577-6369
Richard RomanoInstitute of Transport Studies, University of Leeds, Leeds, United Kingdom.
Natasha MeratInstitute of Transport Studies, University of Leeds, Leeds, United Kingdom.
Gustav MarkkulaInstitute of Transport Studies, University of Leeds, Leeds, United Kingdom.
Richard WilkieSchool of Psychology, University of Leeds, Leeds, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

AutomationAutomobile DrivingMan-Machine SystemsAccidents, TrafficAdultBehaviorChromatography, Thin LayerFemaleHumansMaleReaction TimeVision, Ocular

Identifiers

PMID33253219
PMCPMC7703974

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.