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Record W2182833550 · doi:10.1109/mvt.2015.2481561

Visible Light Communication for Vehicular Networking: Performance Study of a V2V System Using a Measured Headlamp Beam Pattern Model

2015· article· en· W2182833550 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Vehicular Technology Magazine · 2015
Typearticle
Languageen
FieldEngineering
TopicVehicular Ad Hoc Networks (VANETs)
Canadian institutionsWestern University
FundersUniversity of Waterloo
KeywordsHeadlampVisible light communicationContext (archaeology)Light-emitting diodePhotodetectorComputer scienceAutomotive industryPhotodiodeEngineeringTelecommunicationsElectrical engineeringOpticsPhysics

Abstract

fetched live from OpenAlex

In this article, we discuss visible light communication (VLC) in the context of vehicular communication networks. With the omnipresence of light-emitting diodes (LEDs) in outdoor and automotive lightings, VLC emerges as a natural candidate for vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications. We first provide an overview of this emerging research area highlighting recent advances and identifying open problems for further research. Then, we present the performance evaluation of a typical V2V VLC system with realistic automative light sources. Our evaluation takes into account the measured headlamp beam pattern and the impact of road reflected light. We demonstrate that depending on the photodetector (PD) position above the ground level, a data rate of 50 Mb/s can be achieved at 70 m.

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)0.001
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.098
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.033
GPT teacher head0.243
Teacher spread0.210 · 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