MétaCan
Menu
Back to cohort
Record W2042110323 · doi:10.1109/ivs.2012.6232162

Lateral stability analysis of on-road vehicles using Lyapunov's direct method

2012· article· en· W2042110323 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicVehicle Dynamics and Control Systems
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsLyapunov functionControl theory (sociology)Stability (learning theory)YawRollover (web design)Vehicle dynamicsLyapunov redesignComputer scienceMathematicsEngineeringAutomotive engineeringNonlinear systemPhysicsControl (management)Artificial intelligence

Abstract

fetched live from OpenAlex

Vehicle rollover may occur due to the yaw instability. Hence, the yaw stability analysis can help improve vehicle safety. In this paper, Lyapunov's direct method is applied to the lateral stability analysis of the non-linear vehicle model driven in a straight-line with constant longitudinal velocity, where the non-linearity of the model comes from the non-linear expression of the lateral tire forces. Two new Lyapunov functions are proposed. These functions do not explicitly depend on vehicle parameters and estimate the larger stability regions as compared with previous works.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.511
Threshold uncertainty score0.407

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 head0.022
GPT teacher head0.265
Teacher spread0.243 · 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

Quick stats

Citations25
Published2012
Admission routes1
Has abstractyes

Explore more

Same topicVehicle Dynamics and Control SystemsFrench-language works237,207