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Record W2070581493 · doi:10.4271/2012-01-0934

Design and Evaluation of Active Trailer Steering Systems of Long Combination Vehicles Using Driver-Software-in-the-Loop Simulations

2012· article· en· W2070581493 on OpenAlex
Xuejun Ding, Yuping He

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

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2012
Typearticle
Languageen
FieldEngineering
TopicVehicle Dynamics and Control Systems
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsTrailerComputer scienceSoftwareAutomotive engineeringSteering systemLoop (graph theory)Vehicle dynamicsControl engineeringSimulationEngineeringOperating system

Abstract

fetched live from OpenAlex

<div class="section abstract"><div class="htmlview paragraph">Vehicle simulators are often used for vehicle system development and driver behaviour study. The target of this study is to design and evaluate an Active Trailer Steering (ATS) system for a Long Combination Vehicle (LCV) with mutiple trailers using a real-time vehicle simulator. A linear yaw-plane LCV model is generated to derive an optimal ATS controller. Then, the controller is reconstructed in LabVIEW and integrated with a vehicle model for a B-train double from TruckSim. The Driver-Software-in-the-Loop (DSIL) real-time simulations are conducted with the vehicle simulator. The DSIL real-time simulations indicate that the ATS controller can effectively improve the LCV's low-speed maneuverability and high-speed stability under the test maneuvers of a low-speed 90-degree turn and a high-speed single-lane change, respectively. The investigation based on the DSIL real-time simulations paves the road to the future development of electronic control units (ECUs) for the ATS system using Driver-Hardware-in-the-Loop real-time simulations.</div></div>

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)0.002
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.993
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.025
GPT teacher head0.260
Teacher spread0.235 · 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