Drones Delivering Automated External Defibrillators—Integrating Unmanned Aerial Systems into the Chain of Survival: A Simulation Study in Rural Germany

Objective: This simulation study investigated factors influencing sustained performance and fatigue during operation of multiple Unmanned Aerial Systems (UAS). The study tested effects of time-on-task and automation reliability on accuracy in surveillance tasks and dependence on automation. It also investigated the role of trait and state individual difference factors. Background: Warm’s resource model of vigilance has been highly influential in human factors, but further tests of its applicability to complex, real-world tasks requiring sustained attention are necessary. Multi-UAS operation differs from standard vigilance paradigms in that the operator must switch attention between multiple subtasks, with support from automation. Method: 131 participants performed surveillance tasks requiring signal discrimination and symbol counting with a multi-UAS simulation configured to impose low cognitive demands, for 2 hr. Automation reliability was manipulated between-groups. Five Factor Model personality traits were measured prior to performance. Subjective states were assessed with the Dundee Stress State Questionnaire. Results: Performance accuracy on the more demanding surveillance task showed a vigilance decrement, especially when automation reliability was low. Dependence on automation on this task declined over time. State but not trait factors predicted performance. High distress was associated with poorer performance in more demanding task conditions. Conclusions: Vigilance decrement may be an operational issue for multi-UAS surveillance missions. Warm’s resource theory may require modification to incorporate changes in information processing and task strategy associated with multitasking in low-workload, fatiguing environments. Application: Interface design and operator evaluation for multi-UAS operations should address issues including motivation, stress, and sustaining attention to automation.

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Human systems integration: A discrete event simulation of operational utility for control of multiple small unmanned aerial systems

PsycEXTRA Dataset ◽

10.1037/e578862012-006 ◽

2010 ◽

Author(s):

John M. Colombi ◽

Jill R. Ward

Keyword(s):

Discrete Event Simulation ◽

Discrete Event ◽

Systems Integration ◽

Unmanned Aerial Systems ◽

Event Simulation ◽

Human Systems Integration ◽

Aerial Systems ◽

Human Systems

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LIGHTER-THAN-AIR (LTA) UNMANNED AERIAL SYSTEM (UAS) CARRIER CONCEPT FOR SURVAILLANCE AND DISASTER MANAGEMENT

Seminar Nasional Geomatika ◽

10.24895/sng.2018.3-0.1051 ◽

2019 ◽

Vol 3 ◽

pp. 1255

Author(s):

Ahmad Salahuddin Mohd Harithuddin ◽

Mohd Fazri Sedan ◽

Syaril Azrad Md Ali ◽

Shattri Mansor ◽

Hamid Reza Jifroudi ◽

...

Keyword(s):

Unmanned Aerial Vehicles ◽

Disaster Management ◽

Unmanned Aerial Systems ◽

Unmanned Aerial System ◽

Border Control ◽

Aerial Vehicles ◽

Operational Safety ◽

In Situ Methods ◽

Aerial Systems

Unmanned aerial systems (UAS) has many advantages in the fields of SURVAILLANCE and disaster management compared to space-borne observation, manned missions and in situ methods. The reasons include cost effectiveness, operational safety, and mission efficiency. This has in turn underlined the importance of UAS technology and highlighted a growing need in a more robust and efficient unmanned aerial vehicles to serve specific needs in SURVAILLANCE and disaster management. This paper first gives an overview on the framework for SURVAILLANCE particularly in applications of border control and disaster management and lists several phases of SURVAILLANCE and service descriptions. Based on this overview and SURVAILLANCE phases descriptions, we show the areas and services in which UAS can have significant advantage over traditional methods.

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Implementation of Multiple Model: Simulation and Experimentation for Future State Prediction on Different Classes of Small Unmanned Aerial Systems

AIAA Scitech 2021 Forum ◽

10.2514/6.2021-0449 ◽

2021 ◽

Author(s):

James Z. Wells ◽

Rumit Kumar ◽

Manish Kumar

Keyword(s):

Model Simulation ◽

Unmanned Aerial Systems ◽

Multiple Model ◽

Future State ◽

State Prediction ◽

Aerial Systems

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Reliability of Analytically Redundant Systems for Small Unmanned Aerial Systems

AIAA Scitech 2021 Forum ◽

10.2514/6.2021-1178 ◽

2021 ◽

Author(s):

Aditya Kotikalpudi ◽

Edwin A. Williams ◽

Peter J. Seiler

Keyword(s):

Unmanned Aerial Systems ◽

Aerial Systems ◽

Redundant Systems

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Beach and dune impacts due to Hurricane Florence in Dare County, North Carolina

Shore & Beach ◽

10.34237/1008725 ◽

2019 ◽

pp. 44-49 ◽

Cited By ~ 1

Author(s):

Elizabeth Sciaudone ◽

Liliana Velasquez-Montoya

Keyword(s):

North Carolina ◽

Prior Knowledge ◽

Unmanned Aerial Systems ◽

State University ◽

National Wildlife Refuge ◽

Sediment Samples ◽

Wildlife Refuge ◽

Full Report ◽

Aerial Systems

Less than two weeks after Hurricane Florence made landfall in North Carolina (NC), a team of researchers from NC State University traveled to Dare County to investigate the storm’s effects on beaches and dunes. Using available post-storm imagery and prior knowledge of vulnerabilities in the system, the team identified several locations to visit in the towns of Kitty Hawk, Nags Head, Rodanthe, Buxton, and Hatteras, as well as a number of locations within the Pea Island National Wildlife Refuge (Figure 1). Data collected included topographic profiles, still imagery and video from unmanned aerial systems, sediment samples, and geo-located photography. This Coastal Observations piece presents some of the data and photos collected; the full report is available online (Sciaudone et al. 2019), and data collected will be made available to interested researchers upon request.

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