individual

What campus are you from?

Daytona Beach

Authors' Class Standing

Taeyun Yoo, Graduate Student

Lead Presenter's Name

Taeyun Yoo

Faculty Mentor Name

Souza Dias Garcia, Joao

Abstract

Approach stability is a critical factor in ensuring safe flight operations, especially in-flight training environments characterized by varying pilot experience levels. Although flight data recorders (FDRs) offer comprehensive performance data for evaluating approach stability, these devices are typically absent from training aircraft. Consequently, assessments in flight training settings depend predominantly on instructor expertise and subjective evaluation, which restricts the potential for quantitative post-flight analysis. This study investigates the application of open-source Automatic Dependent Surveillance–Broadcast (ADS-B) data to identify and evaluate approach stability within flight training operations. This research develops and tests a metric-based framework for classifying approach stability using publicly available ADS-B trajectory data. The analysis utilizes training operations data from Embry-Riddle Aeronautical University, sourced from the OpenSky Network. Key flight parameters, including altitude, vertical speed, ground speed, and heading, are analyzed to determine quantifiable indicators of stable and unstable approach patterns. Data processing and visualization are conducted in Python to support the preliminary development of reproducible metrics for approach evaluation. The primary objective of this research is to explore the feasibility of a data-driven methodology for assessing approach performance independent of proprietary or subscription-based systems. The proposed framework is intended to serve as an analytical resource for instructors, students, and flight departments, supporting post-flight review, safety education, and data-driven training management. Anticipated outcomes include (1) advancing the use of ADS-B data in flight training safety analysis and (2) providing a basis for developing quantitative criteria that improve consistency and decision-making in flight operations.

Did this research project receive funding support from the Office of Undergraduate Research.

No

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Data-Driven Metrics for Approach Stability Assessment in Flight Training Using ADS-B Data

Approach stability is a critical factor in ensuring safe flight operations, especially in-flight training environments characterized by varying pilot experience levels. Although flight data recorders (FDRs) offer comprehensive performance data for evaluating approach stability, these devices are typically absent from training aircraft. Consequently, assessments in flight training settings depend predominantly on instructor expertise and subjective evaluation, which restricts the potential for quantitative post-flight analysis. This study investigates the application of open-source Automatic Dependent Surveillance–Broadcast (ADS-B) data to identify and evaluate approach stability within flight training operations. This research develops and tests a metric-based framework for classifying approach stability using publicly available ADS-B trajectory data. The analysis utilizes training operations data from Embry-Riddle Aeronautical University, sourced from the OpenSky Network. Key flight parameters, including altitude, vertical speed, ground speed, and heading, are analyzed to determine quantifiable indicators of stable and unstable approach patterns. Data processing and visualization are conducted in Python to support the preliminary development of reproducible metrics for approach evaluation. The primary objective of this research is to explore the feasibility of a data-driven methodology for assessing approach performance independent of proprietary or subscription-based systems. The proposed framework is intended to serve as an analytical resource for instructors, students, and flight departments, supporting post-flight review, safety education, and data-driven training management. Anticipated outcomes include (1) advancing the use of ADS-B data in flight training safety analysis and (2) providing a basis for developing quantitative criteria that improve consistency and decision-making in flight operations.

 

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