Generating Representative Small UAS Trajectories using Open Source Data

Weinert, Andrew; Underhill, Ngaire

doi:10.1109/dasc.2018.8569745

Cited by 12 publications

(9 citation statements)

References 24 publications

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“…Due to the lack of operational flight logs to train a generative model, each trajectory was representative of expected commercial UAS operations and generated based on open source geospatial data [61,62]. Trajectory waypoints followed the terrain and tried to maintain a constant altitude with a tolerance of 25 feet.…”

Section: Demonstrated Use In Simulationmentioning

confidence: 99%

A Quantitatively Derived NMAC Analog for Smaller Unmanned Aircraft Systems Based on Unmitigated Collision Risk

Weinert¹,

Alvarez²,

Owen³

et al. 2020

Preprint

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The capability to avoid other air traffic is a fundamental component of the layered conflict management system to ensure safe and efficient operations in the National Airspace System. The evaluation of systems designed to mitigate the risk of midair collisions of manned aircraft are based on large-scale modeling and simulation efforts and a quantitative volume defined as a near midair collision (NMAC). Since midair collisions are difficult to observe in simulation and are inherently rare events, basing evaluations on NMAC enables a more robust statistical analysis. However, an NMAC and its underlying assumptions for assessing close encounters with manned aircraft do not adequately consider the different characteristics of smaller UAS-only encounters. The primary contribution of this paper is to explore quantitative criteria to use when simulating two or more smaller UASs in sufficiently close proximity that a midair collision might reasonably occur and without any mitigations to reduce the likelihood of a midair collision. The criteria assumes a historically motivated upper bound for the collision likelihood and subsequently identify the smallest possible NMAC analogs. We also demonstrate the NMAC analogs can be used to support modeling and simulation activities.

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Section: Demonstrated Use In Simulationmentioning

confidence: 99%

A Quantitatively Derived NMAC Analog for Smaller Unmanned Aircraft Systems Based on Unmitigated Collision Risk

Weinert¹,

Alvarez²,

Owen³

et al. 2020

Preprint

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“…Fast-time Monte Carlo simulations are often utilized to evaluate the performance of aviation safety systems, such as detect and avoid (DAA) for UAS, for close encounters between aircrafts [2][3][4]. The design and effectiveness of these simulations are dependent on how close encounters are defined.…”

Section: Motivationmentioning

confidence: 99%

“…Encounters and manned aircraft behavior have historically been based on an abundance of radar observations, with these models refined for decades [1][2][3]. However, as UAS are not routinely operating beyond visual line of sight, we cannot characterize UAS encounters using observed aircraft behavior.…”

Section: Motivationmentioning

confidence: 99%

“…However, as UAS are not routinely operating beyond visual line of sight, we cannot characterize UAS encounters using observed aircraft behavior. While independent trajectories of representative UAS behavior can be generated [2,3], an alternative approach to characterize the geometry and feasibility of potential UAS vs. UAS encounters is required for the development and evaluation of DAA safety systems.…”

Section: Motivationmentioning

confidence: 99%

“…The continuing integration of unmanned aerial system (UAS) operations into the National Airspace System (NAS) requires new or updated regulations, policies, and technologies to maintain safety and enable efficient use of the airspace. One enabling technology to help address several UAS airspace integration gaps are airspace encounter models, which have been fundamental to quantifying airborne collision risk for manned and unmanned operation [1][2][3][4][5]. These models represent how aircraft behavior and their relative geometries evolve during close encounters.…”

Section: Introductionmentioning

confidence: 99%

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Method to Characterize Potential UAS Encounters Using Open Source Data

Weinert

2020

Aerospace

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As unmanned aerial systems (UASs) increasingly integrate into the US national airspace system, there is an increasing need to characterize how commercial and recreational UASs may encounter each other. To inform the development and evaluation of safety critical technologies, we demonstrate a methodology to analytically calculate all potential relative geometries between different UAS operations performing inspection missions. This method is based on a previously demonstrated technique that leverages open source geospatial information to generate representative unmanned aircraft trajectories. Using open source data and parallel processing techniques, we performed trillions of calculations to estimate the relative horizontal distance between geospatial points across sixteen locations.

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A Multi-disciplinary Scenario Simulation for Low-Altitude Unmanned Air Delivery

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Schirmer

et al. 2021

Automated Low-Altitude Air Delivery

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DLR is Germany's national centre for space and aeronautics research. Its extensive research and development work in aeronautics, space, transportation and energy is integrated into national and international cooperative ventures. Within this series important findings in the different technical disciplines in the field of space and aeronautics, as well as interdisciplinary projects and more general topics are addressed. This demonstrates DLR's outstanding research competences and capabilities to the worldwide scientific community and supports and motivates international research activities in exploring Earth and the universe, while also focusing on environmentally-friendly technologies and promoting mobility, communication and security.

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Generating Representative Small UAS Trajectories using Open Source Data

Cited by 12 publications

References 24 publications

A Quantitatively Derived NMAC Analog for Smaller Unmanned Aircraft Systems Based on Unmitigated Collision Risk

A Quantitatively Derived NMAC Analog for Smaller Unmanned Aircraft Systems Based on Unmitigated Collision Risk

Method to Characterize Potential UAS Encounters Using Open Source Data

A Multi-disciplinary Scenario Simulation for Low-Altitude Unmanned Air Delivery

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