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Record W580991404

Measuring Benefits of Adaptive Traffic Signal Control: Case Study of Mill Plain Boulevard, Vancouver, Washington

2006· article· en· W580991404 on OpenAlexaboutno aff
Ali Goudarz Eghtedari

Bibliographic record

VenueTransportation Research Board 85th Annual MeetingTransportation Research Board · 2006
Typearticle
Languageen
FieldEngineering
TopicTraffic Prediction and Management Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsBoulevardIntersection (aeronautics)SIGNAL (programming language)Signal timingTraffic signalAdaptive controlTransport engineeringControl (management)MillComputer scienceGeographyEnvironmental scienceReal-time computingEngineeringArchaeologyArtificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

The City of Vancouver, Washington implemented an adaptive control system for traffic signal operations at 12 intersections along Mill Plain Blvd. Performance measurement of this system was the main objective of this research. Link, intersection, and travel-time data were compiled and statistically analyzed. Data observed from travel-time runs (collected via a “floating car”) and data collected from system detectors were used to compare performance of the system in the control case (time of day signal control) and the treatment case (adaptive signal control). This research showed that adaptive traffic signal control generally has a positive impact on the system; however, differences could be observed based on the direction of traffic and volume thresholds. Based on the operational studies, average speed improved up to 25%, the travel time decreased up to 20% and number of stops decreased up to 44% under adaptive control in the eastbound direction. Westbound traffic, however, was impacted…negatively!

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.772
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.046
GPT teacher head0.299
Teacher spread0.253 · 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.

Study designSimulation or modeling
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

Citations8
Published2006
Admission routes1
Has abstractyes

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