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Record W7065363096

Effects of task automation on the mental workload and situation awareness of operators of agricultural semi-autonomous vehicles

2013· dissertation· en· W7065363096 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMspace (University of Manitoba) · 2013
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicElectrical and Electromagnetic Research
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsWorkloadAutomationSituation awarenessTask (project management)TractorHuman factors and ergonomicsTask analysisAgricultural machineryControl (management)
DOInot available

Abstract

fetched live from OpenAlex

The effects of in-vehicle automation and driving assistant systems on the mental workload and situation awareness of drivers have been the interest of many studies; some of the implications of automation in such man-machine systems have been identified. Due to the introduction of advanced automated systems in agricultural machinery, farmers are currently working with semi-autonomous vehicles. A human factors perspective on the design of these systems will ensure safe and efficient operation of such man-machine systems. In this study, a systematic approach was utilized to address human factors issues associated with operating a semi-autonomous agricultural vehicle, and to provide design recommendations. The study was carried out in three stages. First, a task analysis was used to identify tasks associated with operating an agricultural vehicle and to select appropriate experimental variables. Next, a preliminary experiment was performed to validate the test procedure and measurement techniques. Finally, the main experiment was administered. Experiments were conducted using the Tractor Driving Simulator located in the Agricultural Ergonomics Laboratory at the University of Manitoba. Thirty young experienced tractor drivers participated in this study. The experiment investigated the effects of i) vehicle steering task automation (VSTA) and ii) implement control and monitoring task automation (ICMTA) on mental workload and situation awareness of drivers. It was found that ICMTA significantly affected situation awareness (and its underlying components) of the operator. The situation awareness of drivers increased as the automation support level increased, but the highest level of automation, where the participants were out of the task loop, resulted in low situation awareness, similar to the condition with no automation support. VSTA only reduced the attentional demand of the situation, one of the three components of the situation awareness, which had negative effect on overall situation awareness. Based on the results from a subjective mental workload measure, moderate levels of mental workload were reported when the participants were involved in the implement control and monitoring task loop. The highest level of ICMTA reduced the average mental workload by 18%. Reaction time of drivers and number of errors committed by drivers both decreased as the automation level increased.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.694
Threshold uncertainty score0.488

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.201
Teacher spread0.195 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it