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Record W2156434403 · doi:10.1109/itsc.2006.1706857

Evaluating the impacts of changeable message signs on traffic diversion

2006· article· en· W2156434403 on OpenAlexaffabout
S. Foo, Baher Abdulhai

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTraffic Prediction and Management Techniques
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsTransfer (computing)Transport engineeringChristian ministryDownstream (manufacturing)Upstream (networking)Computer scienceTraffic flow (computer networking)DetectorMorningMinistry of TransportEnvironmental scienceEngineeringTelecommunicationsComputer securityOperations managementPolitical science

Abstract

fetched live from OpenAlex

The Ontario Ministry of Transportation has 17 CMS installed strategically upstream of Express-Collector transfer locations on Highway 401 in Toronto, Canada. Motorists are informed by the CMS of traffic conditions downstream of the transfer location to help them decide whether to take the next transfer. Loop detectors are installed at the transfer locations to measure traffic flow. This paper evaluates the impact of CMS messages on traffic diversion using 3 years of loop detector data from 2003 to 2005. We have found that on average a CMS message change can alter the diversion rate by up to around 5%, and can shift up to around 300 vph. These numbers depend strongly on the specific initial and final messages, and on the location of the CMS. Drivers' reactions to CMS messages tend to be higher in the afternoon than in the morning. The impacts of CMS messages on drivers appear to be diminishing over the years

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.362
Threshold uncertainty score0.180

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 head0.028
GPT teacher head0.269
Teacher spread0.240 · 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 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

Citations17
Published2006
Admission routes2
Has abstractyes

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