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Record W2245491501 · doi:10.1504/ijhvs.2015.071683

Braking and steering performance analysis of a road vehicle with active independent front steering

2015· article· en· W2245491501 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.

Bibliographic record

VenueInternational Journal of Heavy Vehicle Systems · 2015
Typearticle
Languageen
FieldEngineering
TopicVehicle Dynamics and Control Systems
Canadian institutionsConcordia University
Fundersnot available
KeywordsAutomobile handlingEngineeringAutomotive engineeringRobustness (evolution)Vehicle dynamicsYawActive safetySimulationActive steeringParametric statisticsControl theory (sociology)Computer scienceControl (management)MathematicsArtificial intelligence

Abstract

fetched live from OpenAlex

Active front steering (AFS) systems help achieve target handling performance through simultaneous applications of steering corrections to both the wheels, but may exhibit limited performance during high-speed manoeuvres. This study explores the effectiveness of an active independent front steering (AIFS) system under application of braking to demonstrate that it could not only overcome the limitation of the AFS but also provide sufficient adhesion reserve for generating longitudinal forces. A simple AIFS controller is synthesised using the yaw rate feedback and the tyres' saturation limits. The simulation results are obtained under a wide range of braking-in-turn manoeuvres in different road conditions. Comparisons of the results with those obtained with the conventional AFS suggested greater effectiveness of the AIFS under high-speed manoeuvres. A parametric study is subsequently conducted to study the robustness of the AIFS performance. The results demonstrated enhanced braking-in-turn performance of the AIFS under conditions where the understeer handling characteristic exists.

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 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 score0.024
Threshold uncertainty score0.615

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
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 head0.215
Teacher spread0.206 · 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