Distributed Conflict Detection and Optimal Four-Dimensional Trajectory Resolution Leveraging Polynomial-Based Methods

This paper presents a methodology for distributed conflict detection and resolution of aircraft following time-dependent flight paths. We use parametric fifth-order polynomial splines to define the full, time-based paths of aircraft. This representation can be exploited to rapidly detect conflicts and calculate optimal resolution solutions that minimize deviations from the original path. Conflicts are identified using a Sturm sequencing procedure and resolutions are found using gradient-based optimization techniques. Simulations show the locally optimal resolution of complex multi-aircraft conflicts and large-scale scenarios. Also, a method of fitting the flight- path model to data sets is presented and flight-path trajectories are shown to accurately represent commercial aircraft trajectories from collected automatic dependent surveillance-broadcast data sets.

Authors

Institutions

Publication Details

Journal
Journal of Air Transportation
Published
2025-02-10
DOI
https://doi.org/10.2514/1.d0450
Citations
1
Primary Topic
Air Traffic Management and Optimization
Type
article
Field-Weighted Citation Impact
4.99

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Distributed Conflict Detection and Optimal Four-Dimensional Trajectory Resolution Leveraging Polynomial-Based Methods

Joshua Miller, Cameron K. Peterson, Austin Stone, John L. Salmon et al.
1 citations
Journal of Air Transportation
Air Traffic Management and Optimization
4.99
article

Distributed Conflict Detection and Optimal Four-Dimensional Trajectory Resolution Leveraging Polynomial-Based Methods

Joshua Miller, Cameron K. Peterson, Austin Stone, John L. Salmon, Michael Klinefelter
article en
1 citations

Abstract

This paper presents a methodology for distributed conflict detection and resolution of aircraft following time-dependent flight paths. We use parametric fifth-order polynomial splines to define the full, time-based paths of aircraft. This representation can be exploited to rapidly detect conflicts and calculate optimal resolution solutions that minimize deviations from the original path. Conflicts are identified using a Sturm sequencing procedure and resolutions are found using gradient-based optimization techniques. Simulations show the locally optimal resolution of complex multi-aircraft conflicts and large-scale scenarios. Also, a method of fitting the flight- path model to data sets is presented and flight-path trajectories are shown to accurately represent commercial aircraft trajectories from collected automatic dependent surveillance-broadcast data sets.

Journal of Air TransportationVol. 33(3)
Brigham Young University (US)
Translational Impacts
Openalex Percentile: Top 7%
Air Traffic Management and Optimization
4.99
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Distributed Conflict Detection and Optimal Four-Dimensional Trajectory Resolution Leveraging Polynomial-Based Methods — Joshua Miller, Cameron K. Peterson, et al. · Journal of Air Transportation (2025) | TGRS Research Map | TGRS