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Record W1984361845 · doi:10.1145/971478.971506

A pneumatic tactile alerting system for the driving environment

2001· article· en· W1984361845 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPsychology
TopicHuman-Automation Interaction and Safety
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsComputer scienceTactile displayTactile sensorComputer visionHuman–computer interactionArtificial intelligenceRobot

Abstract

fetched live from OpenAlex

Sensory overloaded environments present an opportunity for innovative design in the area of Human-Machine Interaction. In this paper we study the usefulness of a tactile display in the automobile environment. Our approach uses a simple pneumatic pump to produce pulsations of varying frequencies on the driver's hands through a car steering wheel fitted with inflatable pads. The goal of the project is to evaluate the effectiveness of such a system in alerting the driver of a possible problem, when it is used to augment the visual display presently used in automobiles. A steering wheel that provides haptic feedback using pneumatic pockets was developed to test our hypothesis. The steering wheel can pulsate at different frequencies. The system was tested in a simple multitasking paradigm on several subjects and their reaction times to different stimuli were measured and analyzed. For these experiments, we found that using a tactile feedback device lowers reaction time significantly and that modulating frequency of vibration provides extra information that can reduce the time necessary to identify a problem.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.822
Threshold uncertainty score0.999

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)0.0150.002

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 head0.033
GPT teacher head0.330
Teacher spread0.297 · 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

Quick stats

Citations85
Published2001
Admission routes1
Has abstractyes

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