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Record W2757860680 · doi:10.1109/tits.2017.2742359

Deconflicted Air-Traffic Planning With Speed-Dependent Fuel-Consumption Formulation

2017· article· en· W2757860680 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Transactions on Intelligent Transportation Systems · 2017
Typearticle
Languageen
FieldEngineering
TopicAir Traffic Management and Optimization
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of CanadaConcordia University
KeywordsFuel efficiencyAir traffic controlCollision avoidanceRouting (electronic design automation)Separation (statistics)Air traffic managementFlight planningOperations researchMathematical optimizationTransport engineeringEngineeringCollisionComputer scienceAutomotive engineeringComputer networkComputer securityAerospace engineeringMathematics

Abstract

fetched live from OpenAlex

This paper discusses a unique formulation for the en-route flight planning problem in a constrained airspace with the objective to minimize costs incurred from earliness, lateness, and fuel-consumption, and to ensure flight safety. Mid-air conflict and collision avoidance, and also minimum separation distance between aircraft and speed-dependent fuel-consumption-rate, are explicitly formulated. A 3D mesh network consisting of waypoints is used to provide alternative routing options for aircraft. The formulation of fuel-consumption-rate as a function of speed as part of the air-traffic planning (ATP) problem is unique in the literature. Moreover, this paper is the first attempt to model the mid-air conflict and collision avoidance as part of the ATP problem. In order to demonstrate the capabilities of the mathematical model, test instances were generated and solved by three different solution strategies. The proposed centralized solution strategy can optimally solve small size instances, similar to the air-traffic around airports to help air-traffic control authorities to manage arrival and departure sequences. Larger networks that include several airports can be solved by the proposed two sequential solution strategies (decentralized and hybrid solution strategies) to help air-traffic planning authorities to manage air-traffic safely and more economically.

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 score0.792
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
Bibliometrics0.0000.000
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 head0.031
GPT teacher head0.254
Teacher spread0.223 · 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