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Record W4316876944 · doi:10.1109/tiv.2023.3237703

Disturbance Observer-Based Cooperative Control of Vehicle Platoons Subject to Mismatched Disturbance

2023· article· en· W4316876944 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

VenueIEEE Transactions on Intelligent Vehicles · 2023
Typearticle
Languageen
FieldEngineering
TopicTraffic control and management
Canadian institutionsUniversity of Waterloo
FundersNational Natural Science Foundation of China
KeywordsPlatoonDisturbance (geology)Control theory (sociology)Stability (learning theory)Computer scienceAccelerationSliding mode controlString (physics)Mode (computer interface)Vehicle dynamicsEngineeringControl engineeringControl (management)Automotive engineeringMathematicsArtificial intelligencePhysics

Abstract

fetched live from OpenAlex

The connected and automated vehicle (CAV) technique is a critical application of intelligent vehicles (IV) and is gaining widespread attention for its prospects of increasing driving efficiency. This paper investigates longitudinal control of vehicle platoons subject to both mismatched velocity disturbance and matched acceleration disturbance. The mismatched and matched disturbances are estimated by a finite-time disturbance observer (DO). Furthermore, two coupled sliding mode platoon controllers are proposed incorporating observed disturbances for longitudinal cooperation of platoons. By using and extending the coupled sliding mode technique, not only closed-loop stability but also string stability is finally proved under bidirectional (BD) and predecessor-following (PF) topologies, respectively. Simulations and an experiment are conducted to validate not only the theoretical effectiveness but also the practical performance of the proposed controllers.

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)0.000
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.582
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.019
GPT teacher head0.229
Teacher spread0.210 · 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