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Record W2371362393 · doi:10.1139/tcsme-2012-0007

REAL-TIME MARK-ON-WINDSHIELD WARNING SYSTEM FOR INTELLIGENT VEHICLES

2012· article· en· W2371362393 on OpenAlexvenueno aff
Chyi‐Yeu Lin, Jinn-Feng Jiang, Yijie Chen, Hung-Tuan Wei, Hou-An Chen

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2012
Typearticle
Languageen
FieldEngineering
TopicAutonomous Vehicle Technology and Safety
Canadian institutionsnot available
Fundersnot available
KeywordsWindshieldIntersection (aeronautics)Computer scienceComputer visionObstaclePoint (geometry)Line (geometry)SightCoordinate systemConstruct (python library)Artificial intelligenceSimulationEngineeringAerospace engineeringMathematicsGeographyPhysics

Abstract

fetched live from OpenAlex

The present study proposes a mark-on-windshield warning system for vehicles that allows the driver to see potentially hazardous objects in front of the vehicle without taking his eyes off the road. An identified target is used to construct the line-of-sight equation based on the coordinate system of the moving vehicle. The explicit equation of the intersection point of the line of sight and the windshield surface is derived using an algebraic method. A warning mark is projected at the intersection point on the windshield by a two-degree-of-freedom laser projector unit, allowing the driver to easily identify the obstacle. An augmented reality verification platform is constructed to demonstrate the feasibility of the proposed system.

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: none
Teacher disagreement score0.912
Threshold uncertainty score0.647

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
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 head0.009
GPT teacher head0.194
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

Citations1
Published2012
Admission routes1
Has abstractyes

Explore more

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