Analyzing Human Factors of Spatial Orientation in Remote Unmanned Ariel Systems

Abstract

Current Federal Aviation Administration goals relative to unmanned aerial vehicle proliferation include the safe and secure integration of these crafts within the infrastructure of National Airspace Systems. The secondary goals related to this broader objective address a diverse array of technological, systems-based, and human pilot oriented factors. Technological considerations are directly coherent to the demand for creating improved areas of infrastructure that can safely accommodate such crafts. Systems-oriented requirements include key policies, training measures, and related variables that prepare both pilots and multi-department personnel for crucial forthcoming changes. Human-pilot based factors pertain to the technical systems and training measures that address key factors that can impact response time, decision-making, and other related performance metrics. This analysis explores current FAA system readiness for unmanned vehicle integration from the standpoint of human pilot spatial orientation and sensory awareness. These variables reason with a human pilot`s response to airspace conditions increasingly defined by unmanned vehicles. Spatial orientation in this respect includes the areas of decision making that involve a pilot`s awareness of his or her craft in the context of surrounding unmanned devices. This report will utilize a mixed methods research design in its exploration of current readiness for major carriers such as Virgin Airlines in the context of the aforementioned methodology. 

Proposal

A qualitative-based methodology alongside an applied statistical oriented method of risk assessment and measurement will analyze the effects on human factors of unmanned aerial systems. This analysis would likely include a combination of traditional assessment alongside projective forms of measurement that take into account the unique influence that they can have on human pilot performance.

Examining the Development of Unmanned Travel 

Objective

Increased proliferation of unmanned aerial vehicles represents a phenomenon that has surpassed the expectations among Federal Aviation Agency planners. A technology that formerly represented a niche once marginally developed now potentially represents a catalyst for profound change across the nation`s national air system (Woo, 2017). One symptom related to this broader course of events pertains to the impacts the design and implementation that Unmanned Aerial Vehicles (UAV) may have on pilot training and readiness. A more direct impact will interfere with a pilot`s ability to navigate airspace increasingly populated by unmanned craft (FAA, 2016). Several variables related to these broader developments might also impact the variable of pilot readiness in various ways. Current technological limitations in terms of onboard equipment in traditional manned craft and similar gaps in current air tower designs might represent one key example (FAA, 2017). A lack of ability on the part of training systems to implement relevant procedures that ready pilots for increasingly complex airspace variables represent another (FAA, 2018). Finally, current limitations in terms of the aviation field`s ability to account for the key human pilot variables of spatial orientation and spatial awareness represents a potential variable that could fundamentally disrupt safe airspace travel and operations in NAS contexts increasingly populated by UAVs (Cropsey, 2018; FAA, 2011). 

Scope

Considerations of human pilot performance, relative to the variables of spatial orientation and sensory awareness represents a complex phenomenon that would need to be evaluated according to multiple angles and perspectives (Woo, 2017). Current models presently employ standards designed to cross-analyze the impact of both technological and physiological variables on these key areas of pilot performance (AFS-800, 2016). Examples in this context include variables of lighting in contexts of both runways and onboard displays; dashboard design and arrangement; pilot seating and positioning factors; tower-to-plane communications; in addition to a range of pilot-specific physiological variables (SRC, 2018). Key examples in the latter category include pilot peripheral and direct vision, response and reaction times, as well as the individual`s capacity for abstract spatial decision making, particularly during in-flight contexts and settings (AVE-100, 2018). 

Emerging models utilized to examine key areas of pilot performance in response to UAV craft incorporate a similar set of variables. However, the relative novelty of UAV craft coupled with the aviation`s current efforts in aligning NAS system factors with the increasing reality of UAV traffic, also make these latter measures somewhat less certain (Pope, 2017). Thus, while the FAA seeks to implement effective and empirically proven modes of human pilot assessment within these evolving conditions, questions of actual human pilot competency relative to spatial orientation and sensory awareness remain somewhat uncertain (FAA, 2014). 

This represents a potential concern given the importance that human pilot performance can have in terms of preventing error, collisions, and similar outcomes, and given the relative unpredictability of human pilot performance in the context of airspaces shared with an increasing number of UAV craft. For that reason, it is imperative for planners to carefully investigate key variables that can impact outcomes within an evolving NAS infrastructure (Avidyne Live, 2010). This study will contribute to these broader discussions by assessing current NAS readiness in terms of measuring and improving pilot performance relative to the domains of human pilot spatial orientation and sensory awareness.   

Methodology

For the purpose of this study, the researcher will rely upon a mixed methods research design in order to explore the guiding research question. This will include the incorporation of a qualitative methodology that relies upon a meta-analysis based framework, as well as a statistical-based assessment that will examine the likely barriers and moral consequences of engineering that could impede the safe integration of UAVs into existing NAS airspace infrastructure, and that also examine the potential impact of each identified variable. The first approach seeks to evaluate current literature in order to arrive at pertinent themes related to this broader task. 

The secondary aspect of the research design seeks to evaluate the scope of the threats introduced against the FAA`s desired outcomes relative to UAV integration. Both separate assessments will then allow the researcher to introduce a series of recommendations deriving from both the qualitative and quantitative research methodology. Collectively, both models will seek to generate new information relevant to multiple agencies within the aviation field and to utilize this emerging data as a way of helping system planners identify potential areas of the needed intervention relative to human pilot performance within evolving airspace. 

Purpose of the Study

This analysis will seek to explore the research question of whether current FAA standards policies, in addition to both existing manned flight and air tower technology, are capable of monitoring or improving human pilot performance, particularly in the areas of spatial orientation and sensory awareness (FAA, 2017). This broader assessment will also include two-key areas of secondary focus. First, the study will determine if current FAA policies have sufficiently taken into account these two dimensions of pilot-based competency. Secondly, it will seek to identify and explore potential gaps that might represent key impediments to defined FAA objectives: namely, the safe and secure NAS integration of UAVs into existing airspace infrastructure (Sparks, 2004). 

In order to achieve these targeted outcomes, this study will rely upon a mixed methods research design. This model will specifically incorporate a qualitative-based meta-analysis alongside a statistical assessment that evaluates the key trends deriving from the initial qualitative assessment. The first part of this research model will carefully examine existing literature and will evaluate these sources for their discussion of the key issues related to its area of focus: i.e. human pilot spatial orientation and sensory awareness in the context of an evolving NAS infrastructure increasingly populated by UAVs. The sources consulted will include works deriving from two main categories: official FAA and related agency publications that describe various areas of pilot training, preparation and technical innovation related to UAV airspace introduction, in addition to technical reports and assessments (USDOT, 2018). Works within this first category will provide a set of doctrinal statements and guided objectives that incorporate pilot training and evaluation as part of a broader set of policies designed to prepare the NAS for key changes. Technical-based analysis reports and similar documents will also be useful in terms of outlining and describing the innovations that seek to help aviation planners prepare for UAV-related impacts. A combination of these reports will also generate a diverse set of findings that discuss human and technological factors that potentially address areas of pilot-oriented spatial orientation and sensory awareness (sUAS News, 2018). 

The findings deriving from the report`s meta-analysis will ultimately result in a set of thematic-based observations that will describe current NAS conditions, including intra-system preparedness for addressing the examined variables. While these will serve a descriptive-based purpose, they will also inform this report`s secondary design. The researcher will specifically address the key risk factors identified by the surveyed literature and will use these as the factors explored by the analysis`s statistical assessment. This approach, specifically, will rely upon a risk management-based model as it will identify (1) the variables most likely to impede safe symptom planning relative to the two human performance measurements and (2) the likely scope of their impact. The researcher will then utilize these findings as the basis for a series of recommendations for FAA intra-agency planners. 

The justification for this topic and its approach can be summarized according to the following key points. First, the topic itself represents a potentially vital issue that can impact targeted FAA objectives relative to the safe and secure integration of UAV craft. As we noted, a human error brought on by lack of sleep, migraines, or undiagnosed disease frequently impacts broader areas of aviation safety and planning, even in the context of operational areas already benefiting from intra-agency planning and decision-making. Secondly, current analyst awareness relative to these human error variables within broader systems preparations for UAV craft integration remains projective in nature. The relative novelty of UAV craft, coupled with the uncertainty of many of the models used to assess pilot readiness within the examined domains, require substantial forms of investigation. Accordingly, this topic represents a vital and underexamined issue from an industry planning and security standpoint. 

The third point of justification relates to the author`s knowledge, current experience, and career-related objectives. The subjects examined will directly relate to my areas of specialization; i.e. human factor-based analysis in the areas of cognition, decision-making, biomechanics, advanced technology, automation, human-oriented design, and aeromedical-based physiology. The topic explored by this report will incorporate several of these areas of discussion and will cross-analyze them in its discussion of the interrelationship between NAS systems planning, technical design and integration, and assessments of human pilot physiology and corresponding areas of aviation-based performance. 

Justifications for this report`s research design include the following points of consideration. First, the complexity of the examined issues requires a mixed methods research design: a model that can explore multiple dimensions of the examined phenomenon. In the context of this study, a mixed methods approach will enable the researcher to generate descriptive forms of qualitative analysis, even as it will also allow for the statistical-based assessment of the themes deriving from the meta-analysis. Secondly, an application of both methodologies will enable the researcher to account for their mutual weaknesses and associative areas of vulnerability. In brief, applications of statistical-based risk modeling will provide a numeric assessment that will contextualize the themes deriving from the qualitative-based meta-analysis. Similarly, the qualitative findings will also provide a degree of depth and contextual data that would be missing in most quantitative-based models. 

Research Question and Hypothesis

As noted, this study`s broader purpose is to examine intra-NAS system readiness relative to the dimensions of human pilot training and preparation in the context of evolving airspace. Its statement accordingly can be summarized according to the following:

RP. Human factors in Unmanned Aerial Systems for safe airspace integration regarding spatial orientation and sensory awareness.

The guiding research question, accordingly, reflects this broader point of inquiry:

RQ Have human factors focusing on spatial orientation and sensory awareness been adequately considered by intra-agency planners in terms of UAS integration into the NAS? If not, what can be done to address this issue?

As previously noted, this report will examine this broader question from three main perspectives. This will include assessments deriving from a qualitative-based meta-analysis, a quantitative-oriented risk modeling-based analysis, and from a comparative application of datasets deriving from the two models. Ultimately, all three analyses will seek to prove or disprove the following guiding hypothesis:

Ho: The domains of spatial orientation and sensory awareness of UAS operators have been adequately considered for safe integration into the NAS by cross-agency planners.

The task of proving this hypothesis will include a triangulated series of datasets corresponding to qualitative, quantitative, and hybrid models of findings. Qualitative assessments will identify the themes deriving from both cross-agency literature and technical assessments indicating multi-system thinker views of this issue. Statistical-based assessments will then measure the likely readiness on the part of multi-systems in terms of addressing these two human-error related areas of consideration. Finally, a hybrid-based examination will provide a mixed set of assessments deriving from both research design elements. 

(Definitions omitted for preview. Available via download)

SPECIALIZATION OUTCOMES: 

This analysis will seek to achieve the objectives associated with the ERU FAA`s capstone project by addressing the following program-related goals in the following ways.

Project Outcomes #1: Demonstrate problem-solving skills using scientific research methods. 

A qualitative-based methodology alongside an applied statistical oriented method of risk assessment and measurement. This project will analyze the technical and conceptual fundamentals associated with UAVs throughout its narrowed assessment of how human pilot-factors might impact the safety and security of multi-craft navigation in the future NAS infrastructure. This report will seek to cross-examine these variables in the context of UAV technical features.

Project Outcome #2:   Demonstrate graduate level writing ability using APA format.

The aforementioned proposal will be written in the required context and format, using APA style writing which includes methodology, purpose, scope, objective, executive assessments, and summaries. Everything will be referenced within the paper itself and following the APA style referencing format at the end of the thesis. 

Project Outcome #3: Demonstrate professional communication and oral presentation skills using appropriate media. 

This proposal will be applicable to the Capstone outcomes in order to fulfill the requirements of this submission. It will be done so using thorough and proven research, edited using resources at my disposal through the university, and submitted using original content and proper formatting.  

Project Outcome #4: Demonstrate the ability to evaluate current industry issues or problems using critical thinking skills. 

This report will achieve this outcome by examining current FAA system readiness in terms of UAV craft integration by specifically identifying the current technologies utilized for addressing human pilot spatial orientation and sensory awareness. 

Project Outcomes #5: Demonstrate the use of technology appropriate to industry requirements.

The author will apply relevant theories in the context of the forthcoming project. Examples will include pertinent AI theory in addition to assessments that examine the impact of automation technology on human pilot physiology and corresponding performance.

Project Outcomes #6: Apply an ethical and professional framework to decision making. 

This analysis will follow these requirements as it addresses its central topic and research question through a combined application of external research and new data generation through its applied design and methodologies. 

Project Outcomes #7: Apply principles of human factors in cognition and decision-making, biomechanics, advanced technology and automation, group dynamics, human-centered design, and aeromedical physiology. 

This analysis will address these requirements by identifying present gaps in terms of FAA system planning for UAV integration. It will be a foundation for recommending specific innovations and policies that can address the human pilot competencies that relate to safe UAV performance and function. 

Summary

Through its focus on current FAA programs that address human pilot spatial awareness and sensory application, this study will address key issues broadly related to UAV craft integration within NAS structures. This area of emphasis will address a core set of human pilot-related factors that could potentially impact the FAA`s objectives for safe and secure UAV integration. This approach will thus generate narrowed sets of data that can be applied to broader and complex decision-making.

References

AFS-800. (2016). AC 90-48D. Pilot's role in collision avoidance. DOT/FAA. Retrieved from https://www.faa.gov/documentLibrary/media/Advisory_Circular/AC_90-48D.pdf

AVE-100. (2018). FAA accepted means of compliance process for 14 CFR part 23. Retrieved from https://www.faa.gov/documentLibrary/media/Advisory_Circular/AC_23_2010-1.pdf

Avidyne Live. (2010). TAS and ADS-B FAQs. Retrieved from http://forums.avidyne.com/tas-and-adsb-faqs_topic95.html

Cropsey, L. (2008). Integrating military unmanned aircraft into the national airspace system. Cambridge, Mass: MIT. 

FAA. (2018). Equivalent levels of safety. Retrieved from http://rgl.faa.gov/Regulatory_and_Guidance_Library/rgELOS.nsf/MainFrame?OpenFrameset.

FAA. (2017). FAA Modernization and Reform Act (P.L. 112-095) reports and plans. Retrieved from https://www.faa.gov/about/plans_reports/modernization/

FAA. (2011). Introduction to TCAS II. Retrieved from https://www.faa.gov/documentLibrary/media/Advisory_Circular/TCAS%20II%20V7.1%20Intro%20booklet.pdf

FAA. (2014). TSO-C147a. Traffic advisory systems (TAS) airborne equipment.

FAA. (2016). Visual line of sight operation. Retrieved from https://www.ecfr.gov/cgi-bin/text-idx?pitd=20160829&node=se14.1.107_131&rgn=div8

Pope, S. (2017). How it works: TCAS II. Flying. Retrieved from https://www.flyingmag.com/how-it-works-tcas-ii

Sparks, J. (2004). Transponders: They make the whole system work. Aviation Pros. Retrieved from http://www.aviationpros.com/article/10386629/transponders-they-make-the-whole-system-work

SRC. (2018). Ground-based sense and avoid radar system. Retrieved from https://www.srcinc.com/what-we-do/radar-and-sensors/gbsaa-radar-system.html

sUAS News. (2018). DeTect HARRIER: Ground based sense-and-avoid radar installed at the Rozas Aerodrome in Spain. Retrieved from https://www.suasnews.com/2018/04/detect-harrier-ground-based-sense-and-avoid-radar-installed-at-the-rozas-aerodrome-in-spain/

USDOT. (2018). System enables drone operators to detect and avoid other aircraft. Retrieved from https://www.volpe.dot.gov/air-traffic-systems-operations/air-traffic-management-systems/ground-based-sense-and-avoid

Woo, S. G. (2017). Visual detection of small unmanned aircraft: Modeling the limits of human pilots. Daytona Beach: Embry-Riddle Aeronautical University.