ACAS sXu: Robust Decentralized Detect and Avoid for Small Unmanned Aircraft Systems

Alvarez, Luis; Jessen, Ian; Owen, Michael P.; Silbermann, Joshua; Wood, Paul

doi:10.1109/dasc43569.2019.9081631

Cited by 33 publications

(18 citation statements)

References 3 publications

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“…By characterizing encounters, we can develop and evaluate systems that mitigate airborne collision risk. These system could be obstacle aware, like ACAS sXu [10], such that when maneuvering to avoid another aircraft, the system will attempt to not inadvertently maneuver into an obstacle. Representing obstacles as part of the simulation would be beneficial for system development, evaluation and deployment.…”

Section: Discussionmentioning

confidence: 99%

“…However, discussion of these Monte Carlo encounters were out of scope for this paper. Additionally, while DAA systems can be obstacle aware [10], our research does not directly support a UAS capability to avoid obstacles. Rather, these results can inform if obstacles should be represented as part of simulated UAS encounters when designing or evaluating DAA capabilities to mitigate the risk of a midair collision between aircraft.…”

Section: Objectives and Contributionmentioning

confidence: 98%

“…This scope was informed by the FAA UAS Integration Office, and the standards activities of International Civil Aviation Organization (ICAO), ASTM F38, RTCA SC-147, and RTCA SC-228. The Airborne Collision Avoidance System (ACAS X) unmanned variants [10,11] were considered as DAA reference architectures, as they are being standardized by the aforementioned organizations.…”

Section: Scopementioning

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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Section: Discussionmentioning

confidence: 99%

Section: Objectives and Contributionmentioning

confidence: 98%

Section: Scopementioning

confidence: 99%

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Method to Characterize Potential UAS Encounters Using Open Source Data

Weinert

2020

Aerospace

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“…Of note, the horizontal separation requirement of 164 ft was adopted in this research, as it was also used in a recent UAV tactical conflict resolution study [52]. In terms of the vertical separation, a range of values have been employed in past studies [53][54][55][56]. However, based on initial test simulations, the vertical separation of 25 ft was found to be suitable for the experiments.…”

Section: Conflict Detection and Resolutionmentioning

confidence: 99%

Constrained Urban Airspace Design for Large-Scale Drone-Based Delivery Traffic

2021

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Large-scale adoption of drone-based delivery in urban areas promise societal benefits with respect to emissions and on-ground traffic congestion, as well as potential cost savings for drone-based logistic companies. However, for this to materialise, the ability of accommodating high volumes of drone traffic in an urban airspace is one of the biggest challenges. For unconstrained airspace, it has been shown that traffic alignment and segmentation can be used to mitigate conflict probability. The current study investigates the application of these principles to a highly constrained airspace. We propose two urban airspace concepts, applying road-based analogies of two-way and one-way streets by imposing horizontal structure. Both of the airspace concepts employ heading-altitude rules to vertically segment cruising traffic according to their travel direction. These airspace configurations also feature transition altitudes to accommodate turning flights that need to decrease the flight speed in order to make safe turns at intersections. While using fast-time simulation experiments, the performance of these airspace concepts is compared and evaluated for multiple traffic demand densities in terms of safety, stability, and efficiency. The results reveal that an effective way to structure drone traffic in a constrained urban area is to have vertically segmented altitude layers with respect to travel direction as well as horizontal constraints imposed to the flow of traffic. The study also makes recommendations for areas of future research, which are aimed at supporting dynamic traffic demand patterns.

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“…For the sUAS these functions required redefinition. Rather than including separate RWC and CA functions, sUAS will include one level of alerting and guidance, with the separation volume based on intruder type [19]. The Well Clear recommendations inform the scalable separation volume, and the considered metrics were probability of a NMAC, probability of loss of Well Clear (PLoWC), horizontal miss distance, and vertical miss distance.…”

Section: A Well Clear Recommendationmentioning

confidence: 99%

Detect and Avoid Considerations for Safe sUAS Operations in Urban Environments

Martinez

Ince

Selvam

et al. 2021

2021 IEEE/AIAA 40th Digital Avionics Systems Conference (DASC)

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Operations involving small Unmanned Aerial Systems (sUAS) in urban environments are occurring ever more frequently as recognized applications gain acceptance, and new use cases emerge, such as urban air mobility, medical deliveries, and support of emergency services. Higher demands in these operations and the requirement to access urban airspace present new challenges in sUAS operational safety. The presence of Detect and Avoid (DAA) capability of sUAS is one of the major requirements to its safe operation in urban environments according to the current legislation, such as the CAP 722 in the United Kingdom (UK). The platform or its operator proves a full awareness of all potential obstacles within the mission, maintains a safe distance from other airspace users, and, ultimately, performs Collision Avoidance (CA) maneuvers to avoid imminent impacts. Different missions for the defined scenarios are designed and performed within the simulation model in Software Tool Kit (STK) software environment, covering a wide range of practical cases. The acquired data supports assessment of feasibility and requirements to real-time processing. Analysis of the findings and simulation results leads to a holistic approach to implementation of sUAS operations in urban environments, focusing on extracting critical DAA capability for safe mission completion. The proposed approach forms a valuable asset for safe operations validation, enabling better evaluation of risk mitigation for sUAS urban operations and safety-focused design of the sensor payload and algorithms.

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ACAS sXu: Robust Decentralized Detect and Avoid for Small Unmanned Aircraft Systems

Cited by 33 publications

References 3 publications

Method to Characterize Potential UAS Encounters Using Open Source Data

Method to Characterize Potential UAS Encounters Using Open Source Data

Constrained Urban Airspace Design for Large-Scale Drone-Based Delivery Traffic

Detect and Avoid Considerations for Safe sUAS Operations in Urban Environments

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