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Record W1904215708 · doi:10.1139/cjce-2014-0489

Long-term evaluation of the operational performance of fixed time ramp metering control strategy: a freeway corridor study

2015· article· en· W1904215708 on OpenAlexvenueno aff
Osama A. Osman, Julius Codjoe, Sherif Ishak, J.J. Asensio Rodríguez, Marlene Russell

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2015
Typearticle
Languageen
FieldEngineering
TopicTraffic control and management
Canadian institutionsnot available
Fundersnot available
KeywordsMetering modeTraffic flow (computer networking)Transport engineeringLevel of serviceSoftware deploymentComputer scienceAutomotive engineeringEngineeringComputer network

Abstract

fetched live from OpenAlex

Ramp metering is one of the successful active traffic control strategies to control traffic flow at entry points to freeways. This study evaluates the effectiveness of fixed-time ramp metering control strategy on the day-to-day operation of traffic over two segments (easternmost and westernmost) of the I-12 corridor in Baton Rouge, Louisiana. Detector speeds and volumes were collected over 11 months and used to generate three performance measures, speed, travel time, and level of service to compare traffic conditions before and after the deployment of ramp meters. Comparative analysis, comprising statistical analysis, analysis of travel time savings, and level of service were then undertaken for traffic conditions before and after ramp meters installation. Overall, the results show some improvements in traffic conditions in the eastbound direction of the westernmost segment; however, the conditions slightly deteriorated on the westbound of the same segment. For the easternmost segment of I-12, no improvement was detected.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.165
Threshold uncertainty score0.530

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 studies0.0000.000
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 head0.018
GPT teacher head0.203
Teacher spread0.185 · 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

Citations6
Published2015
Admission routes1
Has abstractyes

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