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Record W560305715

Weather and Collaborative Decision Making in the Aviation Community: Two “Tactical” Case Study Examples

2013· article· en· W560305715 on OpenAlexaboutno aff
John M. Lanicci, R. E. Haley, Krista M. Rader

Bibliographic record

VenueScholarly Commons (Embry–Riddle Aeronautical University) · 2013
Typearticle
Languageen
FieldEngineering
TopicAir Traffic Management and Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsAviationAeronauticsGroup decision-makingOperations researchComputer scienceEngineeringManagement sciencePolitical science
DOInot available

Abstract

fetched live from OpenAlex

Collaborative Decision Making (CDM) in the aviation community has been defined as a “cooperative effort between the various components of aviation transportation, both government and industry, to exchange information for better decision making” (http://cdm.fly.faa.gov/). Two central tenets of CDM are that better information will lead to better decision-making, and that tools and procedures will enable air navigation service providers and flight operators to respond to changing conditions more readily. CDM can trace its roots to the mid 1990s, when airlines began sharing information about flight schedules with air traffic managers in an effort to determine potential “bottlenecks” in the National Airspace System (NAS) and proactively try to minimize them. Knowledge of mission-impacting weather has long been recognized as an important component of CDM. The main effort in this arena to date has been the development of convective forecasting products (e.g., CCFP) for making decisions about traffic reroutes in the NAS for time periods beyond 2 hours in advance. This timeframe is typically defined as “strategic” in aviation, and the consideration of NAS reroutes due to forecast weather impacts is typically handled at the Air Traffic Control System Command Center (ATCSCC) through a series of collaborative conference calls held with various U.S. and Canadian aviation stakeholders such as major airlines, representatives of business aviation, air route traffic control centers (ARTCCs), traffic approach control facilities in major U.S. metropolitan areas, and forecasters from the Aviation Weather Center and Center Weather Service Units. The meteorological focus has mainly been on convective weather, since it is responsible for major disruptions to many primary air traffic routes across the continental U.S. during the spring and summer months. In contrast to the current weather and CDM focus, this study addresses the topic of weather and CDM from the individual pilot perspective in the more "tactical" arena of preflight planning and enroute execution and decision-making. We present the results of two case studies of aircraft accidents—one general aviation and the other commercial—where there was essentially little to no “collaboration” between the pilot, air traffic control, and the available flight weather services. The general aviation case is a fatal accident over the eastern shore of Maryland in April 2007, and the commercial case is the Colgan Air crash in February 2009. Both cases were analyzed from the meteorological and the weather/CDM perspectives, in the context of pre-flight planning and enroute execution and decision-making. While flight-impacting weather was present in both cases, the weather was not severe enough to have caused the fatal accidents alone, but it was significant enough to have exceeded the pilots' ability to operate in those conditions. In both cases, a limited exchange of weather information between the pilots in command and air traffic controllers and flight weather service providers was insufficient to alert the pilots to the dangers that they would encounter enroute. The study found that while the mission-impacting weather was important, most, if not all aspects of the communication of critical weather information and collaboration between different users in the NAS in the tactical decision-making domain is no different today than it was 20-30 years ago. In both cases, the pilot relied on traditional methods such as paper products and telephone-based briefings to get weather information during pre-flight planning. In flight, the vast majority of weather information was passed via voice communications, which is inefficient, time-consuming, and subject to translation errors. The significance of these findings is put into the context of the upcoming Next Generation Air Transportation System, a cornerstone of which is a robust weather and CDM environment enabled by a “common weather picture” available to NAS users. While progress has been made for strategic planning for NAS impacts, there is a considerable way to go to achieve the same level of advancement for tactical aviation decision-making in both general and commercial aviation, despite technological innovations such as real-time data-linked weather information to the cockpit.

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.

How this classification was reachedexpand

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.341
Threshold uncertainty score0.725

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0000.000
Research integrity0.0000.001
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 head0.021
GPT teacher head0.234
Teacher spread0.213 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2013
Admission routes1
Has abstractyes

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