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Record W2164159470 · doi:10.3141/1791-02

Design and Implementation of Bus–Holding Control Strategies with Real-Time Information

2002· article· en· W2164159470 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueTransportation Research Record Journal of the Transportation Research Board · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicTransportation Planning and Optimization
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsHeadwayReal-time Control SystemControl (management)Point (geometry)Real-time dataSet (abstract data type)Computer scienceTime pointOperations researchSimulationReal-time computingTransport engineeringEngineeringMathematics

Abstract

fetched live from OpenAlex

A systematic study is described to address various design and implementation issues associated with the problem of real-time bus holding control. Two holding control models have been investigated. The first model follows the conventional threshold-based control logic that determines holding times on the basis of headway to the preceding bus. The second model makes use of both preceding and following headways in identifying optimal control decisions with the assumption that real-time bus location information is available for estimating future bus arrivals at the control stop. An extensive simulation analysis is performed using a real-fife bus route operated by the Grand River Transit of the region of Waterloo, Ontario. The simulation results have substantiated several conclusions and yielded new findings on various issues such as where to set the control point, how many control points should be used, what is the optimal control strength, and what is the value of real-time location information.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.428
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0000.003
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.068
GPT teacher head0.380
Teacher spread0.312 · 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