Williams, Carretta, Kirkendall, Barron, Stewart, and Rose (2014) conducted a research study in the selection process of UAS personnel by identifying critical skills, abilities, and other characteristics (SAOCs) needed for an Air Vehicle Operator (AVO) to successfully perform.  Navy, Air Force, and Army subject matter experts (SME) identified 115 SAOCs, and through the Unmanned Aerial Systems Interface Selection and Training Technology (UASISTT) initiative, set to improve the selection and training process of UAS/RPA operators.  Common changes in UAS/RPA operations often happen “on the fly,” so oral comprehension, timesharing, organization, time management, and memorization are what I would consider to be among the most important factors when selecting, certifying, and training UAS operators. 

            To some extent, the size and capability of the UAS should play a role in the qualification requirements for UAS crewmembers/operators, however to what degree is unclear.  Pagen, Astwood, and Philips (2015) presented findings that suggest mishaps rates vary across UAS platforms.   Crewmembers of large UAS such as Global Hawk, Predator, and Reaper have witnessed an accident rate three times higher than other UAS class.  This increased accident rate may be the result of large UAS having the capability to fly higher and faster.   

To operate safely in the complex environment of the NAS, UAS crewmembers need adequate training.  I believe, if UAS training where structured to mirror that of manned aviation, a UAS training-roadmap may be established that will allow crewmembers to achieve a level of safety consciousness needed to operate within the constraints of NAS.

References

Pagen, J., Astwood, R., & Philips, H. (2015, May). Optimizing performance of trainees for UAS manpower, interface, and selection (OPTUMIS): A human systems integration (HSI) approach. In a John Flach (Chair), 18^th International Symposium of Aviation Psychology. Symposium conducted at the International Symposium of Aviation Psychology, Dayton, OH.

Williams, H. P., Carretta, T. R., Kirkendall, C. D., Barron, L. G., Stewart, J. E., Rose, M. R. (2014). Selectionn of UAS personnel (SUPer) phase I report: Identification of critical skills, abilities, and other characteristics and recommendation for test battery development (NAMRU-D Report No. 15-16).  Retrieved from https://apps.dtic.mil/dtic/tr/fulltext/u2/a613545.pdf 

ASCI-638 Module 7 examined UAS accidents and incidents and compared them to accidents and incidents that have occurred in piloted aviation.  Wild, Murray, and Baxter (2016) considered technological issues the primary causal factor in UAS accidents and incidents, not human factor deficiencies.  Research conducted by Joslin (2015) revealed 84% of accidents and incidents involving UAS were contributed to equipment failure – C2 lost link and infrastructure degradation of facilities supporting UAS.  Glussich and Histon’s (2010) study of human interaction with automation revealed that inadequacies in mechanical systems were the leading cause of UAS accidents.  UAS accidents were investigated and finding showed that accidents varied with the level of technology and technological reliability was “consistent with early piloted aviation” (Glussich & Histon, 2010).   

Every aviation operation comes with hazards and risks.  Hazards associated with aviation can range from pilot attitude to the operational environment in which the flight is conducted.  For example, a pilot with an anti-authoritative attitude may cut corners by entering the traffic pattern with non-standard entries, misuse checklists, or operate near cloud layers not legally permitted when weather condition are poor (Rossier, 1999).  Risks involved with aviation cannot be eliminated.  One risk of flight is operating in marginal VFR (MVFR).  MVFR is a weather condition defined as having a ceiling between 1,000 and 3,000 feet and/or 3 to 5 miles visibility.  When operating in MVFR the risk of encountering inadvertent IMC is present and for a pilot that is not instrument rated, this situation could result in spatial disorientation (Namowitz, 2015).

UAS operators are pushing for flight beyond visual line of sight (BVLOS).  To help mitigate risks associated with BVLOS, risk management tools such as the basic risk assessment matrix is helpful.  The risk assessment matrix can aid in evaluating commonly known hazards affiliated with BVLOS operations in terms of probability and severity (Elliot & Shear, 2016).  This tool offers a glimpse of the operation during flight planning stage and useful as a guide in making “a go/no-go” decision.  The risk assessment matrix also provides real-time data to safety and management personnel, which is allows constant monitoring of the operation from a safety standpoint (Elliot & Stewart, 2011).

Human factor issues such as decision and skill-based response to environmental conditions have contributed to the UAS mishap and accident rates.  After investigating further, risk assessment and delay of time sensitive task were among decision-based errors (Glussich & Histon, 2010).  

References

Glussich, D. & Histon, J. (2010, October).  Human/Automation interaction accidents: Implications for UAS operation.  Paper presented at the 29^th Digital Avionics Systems Conference, Salt Lake City, UT.  Retrieved from https://ieeexplore-ieee-org.ezproxy.libproxy.db.erau.edu/document/5655352

Elliot, L. J., & Stewart, B. (2011). Automation and Autonomy in Unmanned Systems. In D. M. Marshall, R. K. Barnhart, S. B. Hottman, & M. T. Most (Eds.), Introduction to unmanned aircraft systems (pp. 100-117). New York, NY: CRC Press.

Joslin, R. E. (2015, January). Insight into UAS accidents and incidents.  Paper presented at the Aviation / Aeronautics / Aerospace International Research Conference, Phoenix AZ.  Retrieved from https://commons.erau.edu/aircon/2015/Friday/14/

Namowitz, D. (2015).  Training tips: The M in MVFR.  Retrieved from https://www.aopa.org/news-and-media/all-news/2015/june/08/training-tip

Rossier, R. N. (1999).  Hazardous attitude, which one do you have.  Retrieved from https://www.aopa.org/news-and-media/all-news/1999/september/flight-training-magazine/hazardous-attitudes

Wild, G., Murray, J., & Baxter, G. (2016). Explore civil drone accidents and incidents to help prevent potential air disasters.  Aerospace, 3(3), 1-11. doi:10.3390/aerospace3030022

Module 6 focused on detect and avoid technology and UAS automation and autonomy.  14 CFR 91.113 is the focal point of Detect and Avoid (DAA), as it spells out the means for “see and avoid” and “well clear” compliance for both manned and unmanned aircraft (Brooks & Cook, 2016).  Sensor fusion and advanced algorithms allow DAA systems to remain “well clear” of other traffic through self-separation (SS) and avoid colliding with another aircraft by employing collision avoidance (CA) techniques.  DAA has 11 sub-functions; depending upon the role the pilot plays within the system architecture determines the level of control he or she possesses within the DAA process.  For example, an automatic DAA system can manage the cycle from target detection to return to course without pilot intervention (Brooks & Cook, 2016).          

For UAS to fully integrate in the NAS there must be an adequate level of automation for the appropriate operation conducted.  Automation can range from the operator controlling all aspects of the flight such as data monitoring, calculations, and decisions – low level automation, to full autonomy, where the machine executes computations and decision-making for all modes of flight (Elliot & Stewart, 2011).    

When it comes to manned versus unmanned operations, I do not believe there to be different considerations.  Take 14 CFR 91.113 for example, it states that no matter the type of flight operation, the aircraft operator is responsible to maintain vigilance as to “see and avoid other aircraft” (Brooks & Cook, 2016).  Whether this is accomplished by human eye or electronically by sensors, compliance with the regulation can be fulfilled.  

It is hard to judge if the aviation industry is currently using an adequate amount of automation.  I believe there should be balance between the degree of automation and amount of control the pilot retains within the system.  The goal of automation is to reduce workload, improve precision, and enhance overall system performance, yet commercial airlines and unmanned aircraft continue to crash even though equipped with advanced and sophisticated automation.  It is hard for me to determine the disconnect.  Elliot and Stewart (2011) mentions the struggle between system designers and system operators when dealing with automation.  From the looks of it, it may be a vicious circle the aviation industry accepts. 

References

Brooks, D., & Cook, S. P. (2016). Detect and Avoid. In D. M. Marshall, R. K. Barnhart, E. Shappee, & T. Most (Eds.), Introduction to unmanned aircraft systems (pp. 298-314). New York, NY: CRC Press.

Elliot, L. J., & Stewart, B. (2011). Automation and Autonomy in Unmanned Systems. In D. M. Marshall, R. K. Barnhart, S. B. Hottman, & M. T. Most (Eds.), Introduction to unmanned aircraft systems (pp. 100-117). New York, NY: CRC Press.

The Guide for Aviation Medical Examiners categorizes medicines as either Do Not Issue (DNI) or Do Not Fly (DNF).  DNI medications are those medicines that should not be giving unless cleared by the FAA.  The list of DNF medicines contain medications that airman should be advised not to take while performing crewmember duties (Federal Aviation Administration, 2019).  The majority of over-the-counter (OTC) medications fall under the umbrella of DNF.  Additionally, safety material should be examined by the airman before taking these medicines, since all medications have the potential to be sedative and cause impairment to cognition.  Although individuals have reported feeling active and perceptive under the influence of OTC medication and believe they are functioning in a normal manner, the effects of drugs are still present.  This has been termed “unaware of impair” (Federal Aviation Administration, 2019)

            Pilots should not assume flying responsibilities while taking OTC medications that bear precaution or warnings labels such as – “it may cause drowsiness or be careful when driving a motor vehicle or machinery” (Federal Aviation Administration, 2019), and pilots should refrain from commencing flight duties until sufficient time has elapsed after the last dose has been administered.  When it comes to self-medicating with sleep aids, airman should heed these label warnings, as sleep aids may pose the most significant risk to the UAS operator.  Currently, OTC sleep aids can impair mental processes and reduce reaction time.  Diphenhydramine is a key ingredient in most OTC sleep aid.  Products like Benadryl contain the active ingredient Diphenhydramine and based on the pharmacologic half-life.  Although individuals claim they feel completely awake, the wait time for Diphenhydramine is 60 hours (FAA, 2019).       

            From a human factors perspective, I believe the most effective mitigative strategies UAS operators can use while performing flight operations are not to exceed personal limitations and conduct a thorough self-assessment.  Operating within the limitations you place upon yourself can reduce unnecessary risk by not allowing yourself to ‘push the envelope.’  A self-assessment performed prior to flight can serve as a last line of defense in ensuring that you are fit to perform your duties in a safe manner (U. S. Department of Transportation, Federal Aviation Administration, 2016).

            Fatigue and stress are in somewhat inter-related – fatigue causes stress, and stress causes fatigue.  Stress is a biological reaction to external demands, both physical and psychological, whereas fatigue is the sensation of tiredness felt at the end of a strenuous event, prolonged excitement, or sleepless night (U. S. Department of Transportation, Federal Aviation Administration, 2016).  Both physiological factors can severely affect the UAS operator because they can lead to a rapid decline in pilot performance at the physical and mental level.  Fatigue can cause disorder and impact decision-making skills.  Stress, on the other hand, causes the chemical release of hormones into the body’s bloodstream, which elevates metabolism in order to feed additional energy to muscles.  Stress also increases blood sugar, heart rate, respiration, blood pressure, and perspiration (U. S. Department of Transportation, Federal Aviation Administration, 2016).  Becoming unable to cope with stress and/or ineffectually at controlling fatigue can be have a detrimental effect on safety.

References

Federal Aviation Administration. (2019, February 21).  Guide for aviation medical examiners.  Retrieved from https://www.faa.gov/about/office_org/headquarters_offices/avs/offices/aam/ame/guide/pharm/dni_dnf/

U. S. Department of Transportation, Federal Aviation Administration. (2016).  Remote pilot – small unmanned aircraft systems study guide (FAA-G-8082-22).  Retrieved from https://www.faa.gov/regulations_policies/handbooks_manuals/aviation/media/remote_pilot_study_guide.pdf

Module 4 weighed heavily on UAS regulations and the legal framework surrounding emerging technology.  The power struggle between federal regulation and state and local laws continues to blur the lines of preemption and present new challenges to UAS integration into the NAS.  State and local laws pertaining to UAS are increasing in number and the scope widening (Walsh, 2017).  Unlike the aircraft manufacturing industry that is heavily, federally regulated, unmanned aircraft manufactures face little to no oversight by government, and the relationship between emerging technology and the principles underlining legal defense has diminished.   With the human element removed from the flight-deck and replaced by a remotely operated pilot, “technological self-reliance challenges the well-established legal principles of duty and causation” and the decision-making process engineered into the software controlling the UAS (Walsh, 2017).  With this said, the other half of Module 4 focused on aviation decision making (ADM) and risk management related to UAS.

Aeronautical decision-making (ADM) is a method used to make decisions in an aviation environment.  This approach is systematic and builds upon the pilot’s mental process to determine, consistently, which course of action best suits a particular situation.  The elementary properties of ADM consist of the ability to recognize how personal attitude can contribute to the overall safety of flight; being able to open up and accept ways which allow behavior to change; understanding stress and how to identify the onset of stress and dealing with effectively; gaining knowledge and building a risk assessment toolkit by utilizing all available sources of information afforded; and measure how effective one’s decision-making abilities are and constantly finding ways to improve and refine ADM skills (U.S. Department of Transportation, Federal Aviation Administration, 2016).   

The ADM and Risk Management involved in UAS operations differ slightly from the techniques used in the manned-flight arena.  What stands out the most regarding UAS ADM and Risk Management is having the cognizance of the technology at hand and being able to identify a software or hardware issue in timely manner before it turns into a hazardous situation which is unmanageable.  It seems UAS operators are limited in the sense of resources that available and must be aware of this limitation and factor it into the risk assessment matrix.

Commercial UAS operations are challenged with some unique issues.  One challenge that comes to mind is resource management.  Depending on the type commercial operation endeavor, one may find him or herself conducting flight operations singlehandedly and lack the resourcefulness needed to cope with an emergency, unlike the resources available to pilots on-board a commercial airliner.  I realize this is comparing apples to oranges; however, I feel that this may be an issue UAS operators with no actual aviation-flight experience should be aware of.  

References

U. S. Department of Transportation, Federal Aviation Administration. (2016).  Remote pilot – small unmanned aircraft systems study guide (FAA-G-8082-22).  Retrieved from https://www.faa.gov/regulations_policies/handbooks_manuals/aviation/media/remote_pilot_study_guide.pdf

Walsh, W. H. (2017). Drone risks create new legal challenges. Risk Management, 64(8), 10-12. Retrieved from http://search.proquest.com.ezproxy.libproxy.db.erau.edu/docview/1938049500?accountid=27203

One of the great challenges foreseen in the integration of UAM into the NAS is safety.  Under the safety umbrella, one aspect of UAM safety is the reliability present in today’s electric propulsion systems.  Battery technology has quickly advanced and continues to make headway as global leader push for clean, green energy.  However, UAM vehicle prototypes are increasing in size and the question is, can battery technology produce the power these larger aircraft demand?  I believe an entirely electric architecture can and will soon support UAM, but if UAM technology is implemented as forecast, I feel that current battery technology is lagging and will not provide an adequate margin of safety.  One alternative solution to UAM propulsion is a gas-turbine based hybrid electric propulsion systems (Norris, 2019).

            The FAA launched its NextGen initiative in 2004 as an attempt to modernize the National Airspace System (NAS).  This initiative includes increasing multiple runway operations, performance-based navigation, satellite-based navigation procedures, and upgraded surface and data communications (Walker, 2014).  Through UTM, UAS should mesh with FAA’s NextGen initiative.  Because UTM is designated as an airspace management tool that aims at providing safe visual and beyond-visual line of sight operations in the low-altitude airspace region, UAS transition into the NAS should be seamless, since the status of airspace can be communicated in real-time through application program interface (API) and not voice (FAA, 2019).

             Detect and avoid (DAA) is the UAS operator’s means of maintaining vigilance in the sky.  By incorporating advanced technology, surveillance sensors play an important role as the pilot’s eyes and mathematical algorithms the pilot’s judgement as to how and when to determine the aircraft is ‘well-clear’ of other airborne traffic (Rorie, 2018).  DAA will be vital as UAS integrate into the NAS.  The DAA technological scheme is the key to UAS successfully integrating into the NAS.

            Loss of communication link between the UAS operator and aerial vehicle while operating in the NAS is a critical and potentially dangerous situation.  One procedure for a lost link scenario is for the aircraft automatically initiate a climb to a designated altitude then track a heading that will return the vehicle to its launch site and land.  During this ‘return-to-home’ procedure, if the communication link is reestablished the vehicle can be redirected on course to complete its mission (Texas Department of Transportation, n/d).   

References

FAA. (2019, February 1).  Unmanned aircraft system traffic management (UTM).  Retrieved from https://www.faa.gov/uas/research_development/traffic_management/

Norris, G. (2019, March 27). Engine makers step up hybrid-electric work to meet UAM demand [Web log post].  Retrieved from https://awin-aviationweek-com.ezproxy.libproxy.db.erau.edu/ArticlesStory/tabid/975/Status/IPAddress/id/455f4630-535b-48ed-b3db-bd2d09bfeaca/Default.aspx

Rorie, C. (2018, March 14).  UAS integration in the NAS: Detect and avoid.  Retrieved from https://ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa.gov/20180002420.pdf

Walker, M. B. (2014, October 9).  FAA, industry agree on high-priority NextGen initiative.  Retrieved from https://search-proquest-com.ezproxy.libproxy.db.erau.edu/docview/1609835700?pq-origsite=summon Texas Department of Transportation. (n/d). Unmanned aircraft systems (UAS) standard operating procedures.  Retrieved from  https://www.dps.texas.gov/docs/prCh4Anx11.pdf

            The ARVL experience of creating and experimenting with different UAS designs was extraordinary, yet at times frustrating.  I marveled at the various design laboratories that facilitated the complete buildup and flight test of selected UAS.  The assembly lab offered the ability to select and evaluate many UAS components, so that an optimal platform can be designed to meet the requirements specific to assigned mission taskings.      

            Regarding performance, ARVL affords the trial-and-error methodology to achieve desired goals.  The powerplant, optics, dynamics, and communication laboratories grant the option of comparing input and output parameters.  However, some of the information presented in the labs were nonapplicable to the scope of this course.  For example, in the dynamic’s lab, changing the X, Y, and Z amplitude and frequency is represented by the sine wave and motion of shake table but seems to provide little insight as to how this data is beneficial to end users such as myself and others enrolled in ASCI 638.

            The missions offered in ARVL are detailed and provide great feedback to the operator, such as whether selected altitude is sufficient to meet obstacle clearance.  The missions provide an introductory insight as how the UAV interacts with the scenario environment, and so far has been the only type of hands-on UAS experience I have received.     

As humans, we interact with machines daily. Technology is becoming an integral part of everyday life and as this technology continues to advances at a rapid pace, we see are selves realizing the great potential such technology as unmanned systems has on modern society. With the advent of unmanned aircraft systems (UAS) comes the challenges of integrating these machines within the National Airspace System (NAS). Challenges in the area of human factors has slowed the pace of UAS implementation as the human-machine interface grows more complex. The primary goal of human factors engineers is to provide safe and non-disruptive flight. As UAS operators continue battling against nonstandard procedures regarding the displays and layouts of current ground control station (GCS) design, efforts to standardize and improve the safety and performance of UAS is at the forefront of ergonomic research and is the baseline to enhance the human-machine relationship.

Thanks for joining me!

Good company in a journey makes the way seem shorter. — Izaak Walton