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Record W2133805337 · doi:10.1002/atr.131

Unconventional USC intersection corridors: evaluation of potential implementation in Doha, Qatar

2010· article· en· W2133805337 on OpenAlexaffvenue
Mohamed El Esawey, Tarek Sayed

Bibliographic record

VenueJournal of Advanced Transportation · 2010
Typearticle
Languageen
FieldEngineering
TopicTraffic control and management
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsIntersection (aeronautics)VisSimChristian ministryTransport engineeringComputer scienceEngineering

Abstract

fetched live from OpenAlex

Abstract Unconventional intersection designs have been recently proposed as a new approach to deal with heavy left turns at signalized intersections. One of these unconventional schemes, the Upstream Signalized Crossover (USC) intersection, was shown to significantly reduce average vehicle delays; particularly when the volumes entering the intersection are relatively high. The Ministry of Public Works of Qatar is considering the implementation of the USC intersection on three signalized intersections along a major urban corridor in Doha. This paper investigates the potential improvements associated with the USC implementation. VISSIM was used to analyze the proposed USC intersections and the existing conventional intersections. Analyses were carried out for AM , Midday, and PM peak hours. The results showed that most of the travel time measurement sections experienced lower delays in the USC configuration for the three peak periods. As well, the total system delay, in hours, for the USC configuration was less than that of the conventional configuration by 19.4, 14.8, and 13.6% for the AM , Midday, and PM peaks, respectively. The average control delay for each single USC intersection was lower than its conventional counterpart by between 7.6 and 22.9%. Copyright © 2010 John Wiley & Sons, Ltd.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.975
Threshold uncertainty score0.320

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 head0.259
Teacher spread0.252 · 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

Citations29
Published2010
Admission routes2
Has abstractyes

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