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Record W2172030581 · doi:10.1109/itsc.2006.1707400

Development of a microscopic traffic simulator for inter-vehicle communication application research

2006· article· en· W2172030581 on OpenAlexaff
Keith Yu Kit Leung, Thanh-Son Dao, Christopher M. Clark, Jan P. Huissoon

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTraffic control and management
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsVisSimFlexibility (engineering)Global Positioning SystemSoftwareComputer scienceTraffic simulationSimulationComputer architecture simulatorSimulation softwareReal-time computingEngineeringMicrosimulationTransport engineeringOperating system

Abstract

fetched live from OpenAlex

This paper describes the development of a microscopic traffic simulator purposely designed for ITS researchers studying inter-vehicle communication (IVC) concepts and applications in large traffic networks. The simulator can represent real life vehicles within the simulation by using data from vehicle Global Positioning System (GPS) receivers, enabling validation of theories with real vehicle data. The software is developed on top of the existing microscopic traffic simulator VISSIM with the added flexibility of modelling and efficiently handling communication between large numbers of vehicles. This along with the software architecture was discussed in detail

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.557
Threshold uncertainty score0.205

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 head0.022
GPT teacher head0.286
Teacher spread0.264 · 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

Citations14
Published2006
Admission routes1
Has abstractyes

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