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Record W2886832304 · doi:10.5539/mas.v12n9p87

Determining Confusion for Traditional and Experimental Pedestrian Signals in Rural and Suburban Areas in the United States

2018· article· en· W2886832304 on OpenAlexvenueno aff
Wakeel Idewu, Dogucan Mazicioglu, Hana Naghawi

Bibliographic record

VenueModern Applied Science · 2018
Typearticle
Languageen
FieldPsychology
TopicSafety Warnings and Signage
Canadian institutionsnot available
Fundersnot available
KeywordsPedestrianSIGNAL (programming language)ComprehensionComputer scienceConfusionComputer securitySimulationTransport engineeringPsychologyEngineering

Abstract

fetched live from OpenAlex

Walking is a mode of travel used by billions of people daily. Facilities that promote walking such as crosswalks often involve sharing space with conflicting vehicular traffic. These areas are not immune to receiving pedestrians that either do not obey or do not understand today’s pedestrian signals, which are used to communicate periods of safe crossing. Therefore, improving comprehension would subsequently improve safety and crash rates. The Traditional Pedestrian Signal in the United States displays an illuminated man and a hand to indicate a cautionary-crossing period, a transition period, and a crossing-prohibited period. This signal type was evaluated and compared to a relatively new Experimental Pedestrian Signal. The Experimental Pedestrian Signal presented in this paper utilized the figure of a walking man changing only by the colors green, yellow, and red. Both signals were analyzed to identify the phases that best communicated the intended action. Video files depicting a Traditional and Experimental Signal were administered with a questionnaire to test the comprehension of rural and suburban participants. The results indicated that the Experimental Pedestrian Signal was not better understood than the current Traditional Signal, although a vast majority of participants preferred the Experimental Signal. The lowest comprehension occurred during the transition phase for both pedestrian signal types. The results also suggest that the interpretation of the yellow color varies by location and may invoke mixed responses if incorporated in pedestrian signals. A more appropriate solution may be to combine both symbolic and color cues into future pedestrian signals.

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)0.001
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 score0.772
Threshold uncertainty score0.271

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.069
GPT teacher head0.318
Teacher spread0.249 · 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 designBench or experimental
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

Citations0
Published2018
Admission routes1
Has abstractyes

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