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Record W2894529794 · doi:10.1177/1541931218621320

Effects of Searching for Street Parking on Driver Behaviour and Physiology: Results From an On-Road Instrumented Vehicle Study

2018· article· en· W2894529794 on OpenAlexaff
Canmanie T. Ponnambalam, Ryan W Cheng, Birsen Donmez

Bibliographic record

VenueProceedings of the Human Factors and Ergonomics Society Annual Meeting · 2018
Typearticle
Languageen
FieldPsychology
TopicHuman-Automation Interaction and Safety
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsWorkloadTransport engineeringTask (project management)Traffic flow (computer networking)Computer scienceEngineeringComputer security

Abstract

fetched live from OpenAlex

Studies regarding street parking have identified safety concerns due to the presence of parked cars, reduced road width, increased and erratic traffic flow, and reduced line of sight. However, few parking-related studies have focused on drivers searching for parking, an often-necessary task that may be considered stressful. An on-road instrumented vehicle study was conducted in an urban environment to assess the effects of searching for parking on driver behaviour and physiology. Twenty-eight participants drove two routes: one with a parking-search task and the other without (baseline condition). When searching for parking, drivers had a significant reduction in their speed, drove closer to the curb and indicated a higher self-reported workload. In addition, there were results approaching significance of increased heart rate and decreased variation in lane position. Further research is needed to determine the potential safety implications of these effects caused by searching for street parking.

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.

How this classification was reachedexpand

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.444
Threshold uncertainty score0.532

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 studies0.0010.000
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 head0.025
GPT teacher head0.325
Teacher spread0.300 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2018
Admission routes1
Has abstractyes

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