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Record W2800220339 · doi:10.1080/00423114.2018.1467018

A practical identifier design of road variations for anti-lock brake system

2018· article· en· W2800220339 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

VenueVehicle System Dynamics · 2018
Typearticle
Languageen
FieldEngineering
TopicVehicle Dynamics and Control Systems
Canadian institutionsConcordia University
FundersNational Natural Science Foundation of China
KeywordsIdentifierBrakeAnti-lock braking systemAutomotive engineeringController (irrigation)Identification (biology)EngineeringLock (firearm)Process (computing)Computer scienceComputer network

Abstract

fetched live from OpenAlex

Emergency brake technologies have always been a major interest of vehicle active safety-related studies. On homogeneous surfaces, traditional anti-lock brake system (ABS) can achieve efficient braking performance and maintain the handling capability as well. However, when road conditions are time variant during the braking process, or different at the bilateral wheels, braking stability performance is likely to be degraded. To address this problem and enhance ABS performances, a practical identifier of road variations is developed in this study. The proposed identifier adopts a statechart-based approach and is hierarchically constructed with a wheel layer and a full vehicle layer identifier. Based on the identification results, modifications are made to a four-phase wheel-behaviour-based ABS controller to enhance its performance. The feasibility and effectiveness of the proposed identifier in collaborating with the modified ABS controller are examined via simulations and further validated by track tests under various practical braking scenarios.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.941
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.015
GPT teacher head0.241
Teacher spread0.226 · 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