Measuring Shared Mental Models in Unmanned Aircraft Systems

2015 ◽  
pp. 1188-1196
Author(s):  
Rosemarie Reynolds ◽  
Alex J. Mirot ◽  
Prince D. Nudze
Keyword(s):  
Mental Models ◽  
Mental Model ◽  
Unmanned Aircraft ◽  
Shared Mental Models ◽  
Unmanned Aircraft Systems ◽  
Unmanned Aircraft System ◽  
Team Coordination ◽  
Shared Mental Model ◽  
Aircraft Systems ◽  
Aircraft System

Unmanned aircraft systems (UASs) are becoming part of the aviation landscape, taking on the dirty, dangerous, or dull operations traditionally completed by military and specialized civil aircraft. These operations often require high levels of team coordination. Team coordination is facilitated when team members share a mental model of group tasks and the individual crewmember's responsibilities in the performance of these tasks. The shared mental model is therefore critical for unmanned aircraft system teams to complete their operational objectives. The ability to forge a shared mental model is complicated by the diverse and often distributed nature of unmanned aircraft system teams. Before strategies can be developed to create accurate shared mental models, researchers must effectively measure shared mental models. This chapter explores the measurement of shared mental models in UASs.

PROSPECTIVE STRUCTURE AND FUNCTIONING OF THE CENTER FOR UNMANNED AIRCRAFT SYSTEMS OF EMERCOM OF RUSSIA

2021 ◽  
pp. 57-61
Author(s):  
Инесса Николаевна Исавнина ◽  
Юрий Николаевич Осипов ◽  
Владимир Иванович Ершов ◽  
Надежда Германовна Каменских
Keyword(s):  
Unmanned Aircraft ◽  
Unmanned Aircraft Systems ◽  
Unmanned Aircraft System ◽  
Aircraft Systems ◽  
Departmental Level ◽  
Aircraft System ◽  
Operating Units

Развитие системы беспилотной авиации, независимо от ее предназначения и структурной принадлежности, предполагает согласованные усилия заинтересованных лиц (руководства, ученых и конструкторов, специалистов испытательных комплексов, преподавателей, инструкторов теоретического и практического обучения операторов управления летательными аппаратами и их полезными нагрузками) по совершенствованию технических характеристик и функционала беспилотных воздушных судов, а также по формированию соответствующих компетенций у персонала эксплуатирующих подразделений. Очевидным является тот факт, что все перечисленные мероприятия наиболее полно могут быть реализованы в рамках функционирования специальных центров развития беспилотных авиационных систем государственного или ведомственного уровня. The development of unmanned aircraft system, regardless of its purpose and structural affiliation, involves the concerted efforts of stakeholders (management, scientists and designers, specialists of test complexes, tutors, as well as theoretical and practical instructors for operators of aircraft and their payloads control) to improve the technical characteristics and functionality of unmanned aircraft, as well as to create appropriate competencies among the personnel of operating units. It is obvious that all these measures can be fully implemented within the framework of special centers for unmanned aircraft systems of state or departmental level.

A neurobiologically-inspired intelligent trajectory tracking control for unmanned aircraft systems with uncertain system dynamics and disturbance

2018 ◽  
Vol 41 (2) ◽  
pp. 417-432 ◽  
Author(s):  
Mohammad Jafari ◽  
Hao Xu ◽  
Luis Rodolfo Garcia Carrillo
Keyword(s):  
System Dynamics ◽  
Real Time ◽  
Uncertain System ◽  
Emotional Learning ◽  
Unmanned Aircraft ◽  
Unmanned Aircraft Systems ◽  
Unmanned Aircraft System ◽  
Trajectory Tracking Control ◽  
Aircraft Systems ◽  
Aircraft System

In this paper, a novel neurobiologically-inspired intelligent tracking controller is developed and implemented for unmanned aircraft systems in the presence of uncertain system dynamics and disturbance. The methodology adopted, known as Brain Emotional Learning Based Intelligent Controller (BELBIC), is based on a novel computational model of emotional learning within brain limbic systems in mammals. Compared to conventional model-based control methods, BELBICs are more suitable for practical unmanned aircraft systems since they can maintain the real-time unmanned aircraft system performance without known system dynamics and disturbance. Furthermore, the learning capability and low computational complexity of BELBIC mean that it is very promising for implementation in complex real-time applications. Moreover, we proved that our proposed methodology guarantees convergence. To evaluate the practical performance of our proposed design, BELBIC has been implemented into a benchmark unmanned aircraft system. Numerical and experimental results demonstrated the applicability and satisfactory performance of the proposed BELBIC-inspired design.

Sound power level and sound pressure level characterization of a small unmanned aircraft system during flight operations

2017 ◽  
Vol 48 (5-6) ◽  
pp. 67-74 ◽  
Author(s):  
Umberto Papa ◽  
Gino Iannace ◽  
Giuseppe Del Core ◽  
Giovanna Giordano
Keyword(s):  
Sound Pressure ◽  
Power Level ◽  
Unmanned Aircraft ◽  
Unmanned Aircraft Systems ◽  
Sound Power ◽  
Unmanned Aircraft System ◽  
Aircraft Systems ◽  
Sound Power Level ◽  
Flight Operations ◽  
Aircraft System

Unmanned aerial vehicles, actually Federal Aviation Administration calls them unmanned aircraft systems, have aroused a great deal for many applications in the scientific, civil, and military sectors. The goal of this article is to evaluate the acoustic emissions of some small unmanned aircraft systems during normal flight operations (e.g. take off, landing, turning, and hovering) related to electric engines and propellers. This analysis will be useful for developing a system (unmanned aircraft systems Tracking and Reconnaissance System), which will be able to locate a small unmanned aircraft system using its sound power level, in a prefixed area. The investigation on sound power levels and sound pressure level is based on EN ISO 3745, which specifies measurement method. The acoustic measurements were carried out in an anechoic room, and the results of each unmanned aircraft system have been presented and discussed.

scholarly journals Acoustic signature measurement of small multi-rotor unmanned aircraft systems

2017 ◽  
Vol 9 (1) ◽  
pp. 3-14 ◽  
Author(s):  
N Kloet ◽  
S Watkins ◽  
R Clothier
Keyword(s):  
Sound Pressure Level ◽  
Sound Pressure ◽  
Urban Environments ◽  
Pressure Level ◽  
Unmanned Aircraft ◽  
Unmanned Aircraft Systems ◽  
Unmanned Aircraft System ◽  
Aircraft Systems ◽  
Acoustic Signature ◽  
Aircraft System

This work describes the testing involved in generating an acoustic signature profile of a small multi-rotor unmanned aircraft system. A typical multi-rotor unmanned aircraft system, with a weight of approximately 2.1 kg, was used for sound pressure level measurements. This study established a relationship between distance, altitude and sound pressure level, finding that the sound decays approximately in line with 6 dB(A) reduction for a doubling of distance. The effect of the orientation of the multi-rotor unmanned aircraft system was also investigated. It was determined that the sound profile does not vary significantly around the periphery of the multi-rotor unmanned aircraft system in the propeller-plane. However, when measured with the observer underneath the multi-rotor unmanned aircraft system, the sound pressure level was found to vary by as much as 10 dB(A), with the greatest sound pressure level at approximately 45° from horizontal. Finally, an acoustic array was used to measure key frequencies for the main sound sources: motors and propellers. It was found that extraneous noise from the multi-rotor unmanned aircraft system frame vibration and mounting methods was also common. Despite relatively low levels of sound being measured (especially when compared with conventional aircraft and rotorcraft), the increasing numbers of unmanned aircraft systems in urban environments, close to humans and dwellings, suggests that increasing complaints are likely. Thus, further research was suggested, including expanding the range of multi-rotor unmanned aircraft system to be tested, introducing DGPS, improving the mounting for indoor testing, and psychoacoustic analysis of the sound.

scholarly journals The integration of compressive sensing and clustering for date gathering in unmanned aircraft system–aided networks

2017 ◽  
Vol 13 (8) ◽  
pp. 155014771772771
Author(s):  
Xiangmao Chang ◽  
Quan Wang ◽  
Zhiguo Qu ◽  
Yanchao Zhao
Keyword(s):  
Energy Consumption ◽  
Sensor Networks ◽  
Compressive Sensing ◽  
Data Gathering ◽  
Unmanned Aircraft ◽  
Unmanned Aircraft Systems ◽  
Sensor Nodes ◽  
Unmanned Aircraft System ◽  
Aircraft Systems ◽  
Aircraft System

The development of the unmanned aircraft systems is envisioned to greatly reduce the energy consumption of sensor nodes in data gathering process using unmanned aircraft systems as mobile sinks. In traditional sensor networks, compressive sensing and clustering are two key energy-efficient techniques for data gathering. However, how to integrate two techniques into the data gathering for unmanned aircraft system–aided wireless sensor networks effectively is still an open problem. Moreover, most clustering schemes focus on the cluster head selection strategy and simplified the problem of cluster member selection, and most compressive sensing schemes are not integrated with the clustering strategy. To this end, this article studies the problem of integrating compressive sensing with clustering for data gathering in unmanned aircraft system–aided networks. We first give a theoretical formulation of this problem. Considering the non-deterministic polynomial-time hard complexity of the problem, we present two algorithms by jointly considering the compressive ratio variation factor and the distance factor to find near-optimal solutions heuristically. Evaluations based on real data traces show that the proposed algorithms greatly reduced the energy consumption of sensor nodes efficiency.

scholarly journals Testing of a Cloud-Controlled Unmanned Aircraft System

2020 ◽  
Vol 32 (1) ◽  
pp. 175-189
Author(s):  
Dávid Ferenc Vránics
Keyword(s):  
Present Article ◽  
Unmanned Aircraft ◽  
Unmanned Aircraft Systems ◽  
Design Development ◽  
Unmanned Aircraft System ◽  
Flight Tests ◽  
Testing Phase ◽  
Aircraft Systems ◽  
Cloud Server ◽  
Aircraft System

During the last years, cloud controlled unmanned aircraft systems (UAS) have become reality. Keeping up with the trend, my research focused on design, development and testing of such a system, while keeping security concerns in mind. The present article summarises the final testing phase, including flight tests and test in lab environment. The most interesting results include successful flight tests with more than 15,000 km communication roundtrip between the ground controller station, the cloud server and the drone; evidences of the importance of georedundant installation of compute hosts to increase survivability of the service; and the demonstration of automatic horizontal scaling of the system depending on performance demands.

Watch For Failing Objects: What Inappropriate Compliance Reveals About Shared Mental Models In Autonomous Cars

2021 ◽  
Vol 65 (1) ◽  
pp. 643-647
Author(s):  
Yosef S. Razin ◽  
Jack Gale ◽  
Jiaojiao Fan ◽  
Jaznae’ Smith ◽  
Karen M. Feigh
Keyword(s):  
Mental Models ◽  
Mental Model ◽  
False Positive Rate ◽  
Ground Truth ◽  
True Positive Rate ◽  
Shared Mental Models ◽  
Shared Mental Model ◽  
Autonomous Cars ◽  
Positive Rate ◽  
Dispositional Factors

This paper evaluates Banks et al.’s Human-AI Shared Mental Model theory by examining how a self-driving vehicle’s hazard assessment facilitates shared mental models. Participants were asked to affirm the vehicle’s assessment of road objects as either hazards or mistakes in real-time as behavioral and subjective measures were collected. The baseline performance of the AI was purposefully low (<50%) to examine how the human’s shared mental model might lead to inappropriate compliance. Results indicated that while the participant true positive rate was high, overall performance was reduced by the large false positive rate, indicating that participants were indeed being influenced by the Al’s faulty assessments, despite full transparency as to the ground-truth. Both performance and compliance were directly affected by frustration, mental, and even physical demands. Dispositional factors such as faith in other people’s cooperativeness and in technology companies were also significant. Thus, our findings strongly supported the theory that shared mental models play a measurable role in performance and compliance, in a complex interplay with trust.

Coexistence Analysis of Civil Unmanned Aircraft Systems at Low Altitudes

Frequenz ◽  
2016 ◽  
Vol 70 (11-12) ◽  
Author(s):  
Yuzhe Zhou
Keyword(s):  
Unmanned Aircraft ◽  
Unmanned Aircraft Systems ◽  
Rate Model ◽  
System Communication ◽  
Aircraft Systems ◽  
Communication Models ◽  
Ratio Criterion ◽  
Coverage Model ◽  
Aircraft System ◽  
Frequency Distance

AbstractThe requirement of unmanned aircraft systems in civil areas is growing. However, provisioning of flight efficiency and safety of unmanned aircraft has critical requirements on wireless communication spectrum resources. Current researches mainly focus on spectrum availability. In this paper, the unmanned aircraft system communication models, including the coverage model and data rate model, and two coexistence analysis procedures, i. e. the interference and noise ratio criterion and frequency-distance-direction criterion, are proposed to analyze spectrum requirements and interference results of the civil unmanned aircraft systems at low altitudes. In addition, explicit explanations are provided. The proposed coexistence analysis criteria are applied to assess unmanned aircraft systems’ uplink and downlink interference performances and to support corresponding spectrum planning. Numerical results demonstrate that the proposed assessments and analysis procedures satisfy requirements of flexible spectrum accessing and safe coexistence among multiple unmanned aircraft systems.

Minimizing Human Factors Mishaps in Unmanned Aircraft Systems

2013 ◽  
Vol 21 (1) ◽  
pp. 25-32 ◽  
Author(s):  
Qaisar R. (“Raza”) Waraich ◽  
Thomas A. Mazzuchi ◽  
Shahram Sarkani ◽  
David F. Rico
Keyword(s):  
Human Factors ◽  
General Purpose ◽  
Unmanned Aircraft ◽  
Unmanned Aircraft Systems ◽  
Ground Control ◽  
Aircraft Systems ◽  
Engineering Standards ◽  
General Purpose Computer ◽  
Aircraft System ◽  
Purpose Computer

Unmanned aircraft system (UAS) mishaps attributable to lack of attention to human factors/ergonomics (HF/E) science in their ground control stations (GCSes) are alarmingly high, and UAS-specific HF/E engineering standards are years away from development. The ANSI/HFES 100-2007 human factors standard is proposed as a specification for the design of UASes because of the similarity between general-purpose computer workstations and GCSes. Data were collected from 20 UASes to determine the applicability of commercial standards to GCS designs. Analysis shows that general-purpose computer workstations and UAS GCSes are up to 98% similar. Therefore, our findings suggest that the application of commercial human factors standards may be a good solution for minimizing UAS mishaps.

scholarly journals Wildland Fire Tree Mortality Mapping from Hyperspatial Imagery Using Machine Learning

2021 ◽  
Vol 13 (2) ◽  
pp. 290
Author(s):  
Dale A. Hamilton ◽  
Kamden L. Brothers ◽  
Samuel D. Jones ◽  
Jason Colwell ◽  
Jacob Winters
Keyword(s):  
Tree Mortality ◽  
Wildland Fire ◽  
Canopy Cover ◽  
Unmanned Aircraft ◽  
Unmanned Aircraft Systems ◽  
Burn Severity ◽  
Crown Fire ◽  
Aircraft Systems ◽  
Ground Truthing ◽  
Aircraft System

The use of imagery from small unmanned aircraft systems (sUAS) has enabled the production of more accurate data about the effects of wildland fire, enabling land managers to make more informed decisions. The ability to detect trees in hyperspatial imagery enables the calculation of canopy cover. A comparison of hyperspatial post-fire canopy cover and pre-fire canopy cover from sources such as the LANDFIRE project enables the calculation of tree mortality, which is a major indicator of burn severity. A mask region-based convolutional neural network was trained to classify trees as groups of pixels from a hyperspatial orthomosaic acquired with a small unmanned aircraft system. The tree classification is summarized at 30 m, resulting in a canopy cover raster. A post-fire canopy cover is then compared to LANDFIRE canopy cover preceding the fire, calculating how much the canopy was reduced due to the fire. Canopy reduction allows the mapping of burn severity while also identifying where surface, passive crown, and active crown fire occurred within the burn perimeter. Canopy cover mapped through this effort was lower than the LANDFIRE Canopy Cover product, which literature indicated is typically over reported. Assessment of canopy reduction mapping on a wildland fire reflects observations made both from ground truthing efforts as well as observations made of the associated hyperspatial sUAS orthomosaic.

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