Human Factors, UAS Remote Warfare and the Ethical and Moral issues involved
Robert J. Winn
ERAU-WW-ASCI638
12/18/2015
Abstract
For millennia, wars have set the stage for the inception and the need for advanced weaponry. Mankind has understood that those with the most advanced technology may surely win a war or at best instill enough fear of retribution in any opponent, that a war should not be undertaken in the first place. From the days of the spear, or bow and arrow to the current unmanned drones that operate in remote areas of the world, mankind will continue to develop weapons that will provide them with a distinct advantage over an enemy. Along with these advancements come the cries for ethical and moral responsibility of those that retain the technology. This paper will address those responsibilities as they pertain to use of unmanned drones in remote arenas and the human factors involved with unmanned aircraft systems (UAS) compared to that of manned fighter operations. Seven technologies that have transformed warfare will be included in the paper and a discussion regarding the continued use of UAS in warfare, and what to expect in regards future improvements of their capabilities.
Keywords: advanced technology, drones, ethics, morality, remote warfare, responsibility, weaponry
Human Factors, UAS Remote Warfare and the Ethical and Moral issues involved
War has a long history that dates back to the dawn of civilization, but armies have come a long way since the spear, or the bow and arrow. Advances in technology have led to faster airplanes, laser-guided weapons, and unmanned, bomb-carrying vehicles (Chow, 2013). But none of these technologies have been introduced without relentless discussions by those claiming these advanced weapons should be wielded without some ethical or moral responsibility.
The most recent advancement in weaponry used today is that of the unmanned aircraft system (UAS) or most commonly referred to as a Drone. It has not been exempt in any means from those discussions regarding ethical and moral responsibility, but by nature of its “unmanned” perception has drawn even more attention by critics.
In order to grasp an understanding of how drones provide a higher level of responsibility than that of their predecessors, six other technologies that have transformed warfare have been presented.
As with any new technology, human factors issues associated with that technology arise. UAS have introduced human factors not previously seen by manned operations performing the same missions. How these human factors are mitigated will be addressed by any future advancement to the technology.
Culture and Values
Sociologists define culture as the beliefs, values, behaviors and material objects that define a people’s way of life. (Macionis, 1995, p. 62). A cultures or societies values are further defined by their ethics and morals or their perception of right or wrong.
Ethics
The field of ethics (or moral philosophy) involves systematizing, defending, and recommending concepts of right and wrong behavior. Ethics, as a theory, has been divided into many fields of study; Metaethics, normative ethics and applied ethics, the latter of which involves examining specific controversial issues such as nuclear war and the use of drones in remote warfare. It is from this area of study that determines how societies shape their opinions of what is right or wrong with wars and how technologies should or shouldn’t be used in them.
The Seven
Denise Chow presented in her article 7 Technologies that transformed warfare (2013) each of these technologies have presented their own ethical, moral as well as human factor issues:
• Drones- Combat drones, or unmanned aerial vehicles, enable troops to deploy weapons in war while safely remaining thousands of miles away from the front lines of the battlefield. As such, the lives of drone pilots are not in danger, which helps the military limit the number of combat fatalities.
• Fly-by-wire- Fly-by-wire technology replaces manual flight controls with an electronic interface that uses signals generated by a computer and transmitted by wires to move control mechanisms. The introduction of fly-by-wire systems in aircraft enabled more precise computer guidance and control.
• Submarines- Submarines revolutionized naval warfare by introducing underwater vessels capable of attacking enemy ships. The first successful submarine attack on a warship occurred during the American Civil War, which lasted from 1861 to 1865. In February 1864, the Confederate submarine CSS H.L. Hunley sank the USS Housatonic in the waters off South Carolina.
Today, the military uses submarines to carry missiles, conduct reconnaissance, support land attacks, and establish blockades.
• Tomahawk missiles- The Tomahawk is a type of long-range cruise missile designed to fly at extremely low altitudes at subsonic speeds, enabling the weapons to be used to attack various surface targets. These jet engine-powered missiles were first used operationally during Operation Desert Storm in 1991. The missiles travel at speeds of approximately 550 miles per hour (880 km/h), and use GPS receivers to pinpoint their targets more accurately.
• Stealth aircraft- Stealth aircraft help pilots evade detection in the sky. While planes cannot be completely invisible to radar detection, stealth planes use a range of advanced technologies to reduce the aircraft's reflection, radio frequency spectrum, and radar and infrared emissions. Stealth technology increases the odds of a successful attack, since enemies have a harder time finding, tracking and defending against these aircraft.
The development of stealth technology likely began in Germany during World War II, but some of the most well-known modern examples of American stealth aircraft include the F-35 Lightning II, the F-22 Raptor and the B-2 Spirit.
• Space weapons- Space weapons include a range of warheads that can attack targets on Earth from space, intercept and disable missiles traveling through space, or destroy space systems or satellites in orbit. During the Cold War, both the U.S. and the former Soviet Union developed space weapons, as political tensions escalated.
While the militarization of space remains controversial, the U.S., Russia and China have developed anti-satellite weapons. Several test firings of these warheads have been successful in destroying satellites in orbit, including a 2007 Chinese anti-satellite missile test that destroyed one of the country's defunct weather satellites.
• Nuclear Weapons- Nuclear bombs are mankind's most destructive weapons. The world's first nuclear weapons, or atomic bombs, were developed by physicists working on the Manhattan Project during World War II.
The Manhattan Project, which began in 1939, has become one of the most well-known secret research programs. The first nuclear bomb was detonated on July 16, 1945, the explosion created a massive mushroom cloud, and the bomb's explosive power was equivalent of more than 15,000 tons of TNT.
In August 1945, two atomic bombs were dropped on Hiroshima and Nagasaki in Japan. The bombings effectively ended World War II, but ushered in decades of global fear of nuclear annihilation. To date, the bombings of Hiroshima and Nagasaki remain the only uses of nuclear weapons in war.
Human Factors
There are numerous human factors associated with both manned and unmanned weapons systems. However, one distinct advantage of using unmanned drones in remote warfare is that it takes the limitations of manned (pilot–on–board) operations out of the equation. No longer are the flight restrictions of manned operations a factor. The drone can remain airborne for as long as its capabilities will allow, where operations of manned weapons are restricted by the physical capabilities of the pilot over longer periods of time.
This allows for more precise targeting, as the drone can hover over a target for longer periods of time to ensure that a target has been positively identified and when the decision to “take-it out” has been given, the target has been isolated as much as possible to reduce the effects of collateral damage.
Artificial Intelligence
Reg Austin (2010) suggested “the study of Artificial Intelligence probably began in the 1930s and has enjoyed a roller-coaster ride in similar fashion to that of UAS development. One is a bottom-up approach which attempts to develop neural networks akin to the operation of the human brain. The other, known as top-down, attempts to simulate the performance of a human brain by using high speed computer algorithms”. Until the Micro-Control Processor or brain of the UAS has been improved neither of these approaches will be proven.
When and if that that day comes, the implementation of this advanced technology in future wars will be decided by the ethics and morals of a global society, which must consider allowing a weapon to think for itself and target the very species that created it.
References
Austin, R. (2010) Unmanned aircraft systems : UAVs design, development and deployment Reston, Va. : American Institute of Aeronautics and Astronautics ; Chichester : Wiley, c2010.
Chow, D. (2013) 7 Technologies that transformed warfare LiveScience, November 19, 2013 Retrieved from http://www.livescience.com/41321-military-war-technologies.html
Macionis, J. J. (1995) Sociology 5th edition, Culture Chapter 3,What is Culture?, By Prentice –Hall Inc.
Sunday, December 20, 2015
Friday, December 18, 2015
9.7 - Blog: Case Analysis Effectiveness
For the past 9 weeks, I have been an active student enrolled in the Embry-Riddle Aeronautical University-WorldWide-ASCI638 Human Factors in Unmanned Systems course. During this time, the other students and I were required to perform and present a case analysis of a subject of our own choosing relating to the numerous human factor issues that are associated with both manned and unmanned operations. The case report needed to demonstrate our understanding of the course topics by analyzing, evaluating, and developing recommendations for addressing an issue associated with human factors in the realm of unmanned aerial systems operations. We were required to retain a connection to a minimum of five course learning outcomes. We needed to identify an underlying issue or problem and propose a recommendation or hypothesis to mitigate the issue. I chose to perform my case analysis on Human Factor Challenges Associated with Maintenance of Unmanned Aircraft Systems.
The foundation of my 35+ years in aviation is maintenance and due in part to my current position as an Airworthiness Inspector assigned to the UAS Integration Office located in Washington, D.C.; I felt the subject matter was something that I could clearly sink my teeth into. During my research I became more familiar with human factors issues surrounding unmanned launch, recovery, long duration operations, fatigue, human performance, Ground Control Station (GCS) design, use of automation, Situation Awareness (SA), Crew Resource Management (CRM), integration into the National Airspace System (NAS), attitudes and perspectives of both government agencies and public entities, use of technology to compensate for no-pilot-onboard, and regulatory issues and solutions.
What I was surprised to learn thru my research was that analysis of maintenance failures associated with Human Factors in unmanned aircraft systems is not on the front table for discussion. I attributed this lack of available information to be directly related to the rapid advancements in technology regarding these systems and the regulators, manufacturers and operators inability to keep up with the continued airworthiness requirements for what is assumed by most of those players and the general public to be either a toy or a mindless drone that requires no additional oversight regarding maintenance activity. In my personal opinion this attitude may prove to be a grave mistake.
Regarding the case analysis as a tool that will benefit my current or future career:
• I found the process of collecting significant data to support my identified problem and proposed mitigation's similar to how I approached resolving issues in my previous two FAA assignments as 1) a manufacturing Inspector and 2) a Maintenance Review Board Chairman assigned to the Aircraft Evaluation Group (AEG). In both of those positions when presented an issue that needed clarification and/or a regulatory response (as would always be the case) I relied on the Regulations, Advisory Circulars, Orders (Inspector guidance) and personal experience to provide a response that was within regulatory guidance and mitigated issues based on a risk based approach.
My only recommendation to enhance the learning experience would be to allow for a final peer review of pre-selected case analysis reports. Not only would it offer feedback to the author on the final/post draft paper, but provide additional theoretical perspectives for the reviewer. Sounds heavy doesn’t it?
The foundation of my 35+ years in aviation is maintenance and due in part to my current position as an Airworthiness Inspector assigned to the UAS Integration Office located in Washington, D.C.; I felt the subject matter was something that I could clearly sink my teeth into. During my research I became more familiar with human factors issues surrounding unmanned launch, recovery, long duration operations, fatigue, human performance, Ground Control Station (GCS) design, use of automation, Situation Awareness (SA), Crew Resource Management (CRM), integration into the National Airspace System (NAS), attitudes and perspectives of both government agencies and public entities, use of technology to compensate for no-pilot-onboard, and regulatory issues and solutions.
What I was surprised to learn thru my research was that analysis of maintenance failures associated with Human Factors in unmanned aircraft systems is not on the front table for discussion. I attributed this lack of available information to be directly related to the rapid advancements in technology regarding these systems and the regulators, manufacturers and operators inability to keep up with the continued airworthiness requirements for what is assumed by most of those players and the general public to be either a toy or a mindless drone that requires no additional oversight regarding maintenance activity. In my personal opinion this attitude may prove to be a grave mistake.
Regarding the case analysis as a tool that will benefit my current or future career:
• I found the process of collecting significant data to support my identified problem and proposed mitigation's similar to how I approached resolving issues in my previous two FAA assignments as 1) a manufacturing Inspector and 2) a Maintenance Review Board Chairman assigned to the Aircraft Evaluation Group (AEG). In both of those positions when presented an issue that needed clarification and/or a regulatory response (as would always be the case) I relied on the Regulations, Advisory Circulars, Orders (Inspector guidance) and personal experience to provide a response that was within regulatory guidance and mitigated issues based on a risk based approach.
My only recommendation to enhance the learning experience would be to allow for a final peer review of pre-selected case analysis reports. Not only would it offer feedback to the author on the final/post draft paper, but provide additional theoretical perspectives for the reviewer. Sounds heavy doesn’t it?
8.7 HUMAN FACTOR CHALLENGES ASSOCIATED WITH MAINTENANCE OF UNMANNED AIRCRAFT SYSTEMS
Running head: HUMAN FACTOR CHALLENGES 1
Human Factor Challenges Associated with Maintenance of Unmanned Aircraft Systems
Robert J. Winn
Embry-Riddle Aeronautical University-WW-ASCI 638
Abstract
The expeditious pace with which Unmanned Aircraft Systems (UAS) are being introduced into the National Airspace System (NAS) presents many challenges. In meeting these challenges, the Federal Aviation Administration (FAA) as mandated by congress in the FAA Modernization and Reform Act (FMRA) of 2012, was tasked to “develop a comprehensive plan to safely accelerate the integration of civil unmanned aircraft systems into the National Airspace System.” Once integration has been achieved, processes and procedures addressing continued airworthiness of UAS must be developed, achieved and understood in order to keep these systems, as well as the general public, property and the NAS safe. Unfortunately, due to the fast pace with which these unmanned systems have been introduced previously established maintenance programs applicable to manned aviation do not address those aspects particular to unmanned programs. The dissimilarities between manned and unmanned systems, have called attention to numerous Human Factor issues. This case study will introduce Human Factors that are associated with these systems, present accident data and the challenges associated with unmanned aircraft systems maintenance programs.
Keywords: airworthiness, human factors, maintenance, public, safety, unmanned aircraft system,
Human Factor Challenges Associated with Maintenance of Unmanned Aircraft Systems
The Federal Aviation Administration (FAA) as mandated by congress in the FAA Modernization and Reform Act (FMRA) of 2012 was tasked to “develop a comprehensive plan to safely accelerate the integration of civil unmanned aircraft systems into the National Airspace System.” Once integration has been achieved, processes and procedures addressing continued airworthiness of UAS must be developed, achieved and understood in order to keep these systems as well as the general public, property and the NAS safe. These processes and procedures will be addressed in regulations to ensure UAS are maintained in an airworthy condition.
The regulations must address the airworthiness of the UAV, qualifications of the operator (pilot), and any special operating rules when the UAV cannot meet the same requirements as manned aircraft (Cooke,2006). But the issue is that the regulations are developed after UAS integration into the NAS has already taken place.
The following section is taken directly from the FAAs Roadmap for UAS integration. It clearly shows that certification of UAS airframes is not on the radar until 2020/2030 and that research is still needed to support any regulations to ensure the continued airworthiness of the airframe /system.
3.2 Airframe Certification
Description of the challenge: Enable the rapid and affordable airframe certification for all types of UAS through increase emphasis on structural analysis and reduction in airframe testing. The existing basis of certification does not cover the new and novel materials and manufacturing processes being used in the manufacturing of UAS. As these methods and materials continue to evolve, research is needed to support an airworthiness determination and continue to ensure airworthiness over the life of the aircraft.
Goals:
Goal 1: Certify an airframe by analysis verified by test, 2020
Goal 2: Develop certification standards for advanced materials and structural design, 2020
Goal 3: Continued airworthiness through onboard health monitoring, 2030 (Roadmap, 2012).
Unfortunately, due to the fast pace with which these unmanned systems have been introduced to the general public, previously established manned maintenance programs do not address aspects significant to unmanned systems. The dissimilarities between manned and unmanned systems have called attention to numerous Human Factor issues. Human factors are a multidisciplinary approach to examining system design, training, experience, and individual motivation, with the objective of positively influencing human performance (USI, 2015). Two conceptual models used to analyze those human factor issues and for assessing and mitigating human factors in aviation maintenance are presented below.
SHEL
The original SHEL concept was developed using the first letters of each basic component, Software, Hardware, Environment and Liveware. The ICAO SHELL model (Fig. 1) introduced by Hawkins in 1975 illustrates how the concept is structured by conjoined blocks.
Figure 1 SHELL model
Source http://www.skybrary.aero/index.php/File:Liveware.jpg
This building block diagram is only intended as a basic aid to understanding Human Factors:
• Software - the rules, procedures, written documents etc., which are part of the standard operating procedures.
• Hardware - the Air Traffic Control suites, their configuration, controls and surfaces, displays and functional systems.
• Environment - the situation in which the L-H-S system must function, the social and economic climate as well as the natural environment.
• Liveware - the human beings - the controller with other controllers, flight crews, engineers and maintenance personnel, management and administration people - within in the system.
PEAR
In an article published in April 2007, Dr. William Johnson presented another conceptual model, where PEAR is used to recall four considerations for assessing and mitigating human factors in aviation maintenance:
• People who do the job; where Physical, Physiological, Psychological and Psychosocial factors are examined.
• Environment in which they work; considers the Physical and Organizational aspects
• Actions they perform; considers the WHAT (i.e. steps, performance, amount of people, communication [oral, visual, written] and information control requirements
• Resources necessary to complete the job. Considers procedures/work cards, Manuals/bulletins/FARs, Test equipment, Tools, Computers, paperwork /signoffs, Ground handling Equipment, Fixtures, materials, task lighting additional manpower and training.
Much like the building blocks in the SHELL model, the PEAR model provides basic factors to facilitate examination of a specific maintenance program. If those areas are weak or robust in nature they will be identified. This information is necessary to ensure that appropriate mitigations to correct them are implemented.
Hurdles
The Unmanned Safety Institute (USI) published a course workbook Building Safe sUAS Organizations (2015) which identified problems associated with UAS technology;
• The explosive number of systems available on the market combined with the relative low barriers to entry has attributed to UAS operations in the NAS as being crowded and dangerous.
• Many of the commercial UAS operators are amateurs turned “professional” and operate with complete ignorance of regulations and guidance.
• Even those who wish to comply with the regulations lack the aviation backgrounds and do not know where or how to begin.
• Those with manned aviation backgrounds find the unmanned systems challenging.
• Original Equipment Manufacturers are new to the aerospace industry and lack the ability to adapt to continued airworthiness requirements.
System Description
A description of a manned system is not very complicated. The aircraft or fuselage is the core component which facilitates the power supply/engine(s), fuel, communication/navigation equipment and provides a command and control platform for the pilot(s) free from external environmental distractions.
Unmanned systems are significantly different, in that the “system” consists of these primary separate components;
• Air vehicle
• Control station
• Payload
• Navigation Systems
• Communications –up/down data links
• Launch and Recovery equipment
• Operator/Pilot
UAS Incident Data
As with any new technology rushed to market, the UAS industry has been plagued by failures at a rate of approximately 1 in every 200 flying hours. These failures are directly related to lack of system standards, certification and poor maintenance oversight.
About 80% of maintenance mistakes in manned aviation involve human factors and if not detected would lead to accidents. Reports regarding unmanned aircraft (UA) accidents have been shown to be higher than that of manned aviation. In order to improve the safety of these systems identifying and understanding the factors involved must be accomplished. The most reliable source for UA accident data currently is the military. The military has a relatively long history of UA use and is diligent in accurately recording information pertaining to accidents/incidents (Williams, 2004).
Accident Data/Classification
The military takes a two-step approach in the classification of UA accidents. The first step takes a rather broad approach to identify those accidents that were attributed to Human factors (Liveware/People) or system component failure (hardware). Within this first step a “Maintenance” category is included to identify those accidents directly attributed to maintenance personnel. In the second step, those accidents classified as related to human factors were classified according to specific human factors issues that are commonly addressed in current research (Williams, 2004).
Data classification from the U.S Army Hunter program shows that accidents attributed to the Aircraft (hardware) accounted for 50% of the Hunter accidents. However, the data also shows that Human Factors and Maintenance errors combined for 56% of the programs accidents. Data, associated with U.S Air Force Predator failures attributes Maintenance (17%), Human Factors (67%) and Aircraft (42%) as the causal factors.
Knowledge
In the book, Introduction to Unmanned Aircraft Systems, by Barnhart, Shapee and Marshall (2011) it was presented that new UAS and their technologies do not fit neatly into the currently accepted training programs, programs that have been proven effective for manned operations. Additionally, these flight systems are being produced faster than the existing flight-training regime can react to them. To compound these training deficiencies, new technology systems that perform similar functions do not look alike and operator interactions with these systems often are completely different. A case could be made that these same issues, regarding the inability to keep up with rapid technological advances, associated with unmanned systems would also be realized by those responsible for the continued airworthiness and maintenance of these systems.
System Maintenance
Maintenance activities are classified into two categories, that of scheduled and unscheduled maintenance, each with its own challenges. Scheduled tasks include routine inspections, adjustments, and time replacements of components. Although the distinction between scheduled and unscheduled maintenance is widely used in the aviation industry, UAS operators do not tend to make a clear distinction between the two. This is partly because in the absence of maintenance procedures, virtually all maintenance tasks are unscheduled (Hobbs, 2008).
Scheduled
Scheduled or preventative maintenance is normally accomplished during a prescribed schedule, recommended by the system manufacturer and or developed by the operator. Conducting these inspections and performing the required maintenance tasks are essential to ensuring that those parts and or systems that have a life limit or known time between failure (TBF) rate are addressed. Scheduled tasks tend to be performed frequently and become familiar, routine activities for the technician. The routine nature of such tasks can increase the chances of absent-minded errors such as memory lapses (Hobbs, 2008).
Unscheduled
Unscheduled maintenance is just what it sounds like. It is a required action due to a mishap where damage was incurred by the system, or requires maintenance be performed to conduct an analysis and repair of a system or hardware failure. Fault identification and diagnosis can be a time-consuming part of UA maintenance, particularly when faults involve avionics or computer systems (Hobbs, 2008).
Due to the lack of manufacturing procedures and guidance unscheduled maintenance can impose undue stress on the mechanic or operator as the lack of a general understanding of the system or repair requirements can cause a significant delay in meeting operational (airtime)/customer induced expectations.
Maintenance Challenges
UAS maintenance is defined as any activity performed on the ground before or after flight to ensure the successful and safe operation of the system. Small UAS maintenance bears little similarity to conventional aviation maintenance as it is currently unregulated, and is rarely performed by personnel with formal maintenance qualifications. (Hobbs, 2008).
In July 2013, the FAA published Unmanned Aircraft Systems (UAS) Operational Approval Notice 8900.227 which stated that UAS Maintenance Qualifications, ratings and training requirements would be established as more data is collected and a regulatory guideline is developed. To date commercial sUAS operators are only required to make a self-certifying statement that the UAS will be maintained in an airworthy condition for operation in the NAS. However, no verification by the FAA is conducted to ensure that the operator has the training or knowledge to show an understanding of what “airworthy” means or that adequate inspection and maintenance procedures have been developed by the manufacturer or the operator to ensure the continued airworthiness of the system.
The bottom-line, the general public lacks the training and understanding that is required to ensure that an “aircraft” and its systems are in a condition for safe operation. This is even more of an issue due to proliferation of these systems available to the untrained public.
The complexity of these systems combined with relatively low reliability will translate into higher mishap rates and higher risk. It is therefore imperative that before and after every flight the system must be inspected for damage or malfunctioning equipment. It is equally important that the system is transported and stored in a safe and secure location (USI, 2015).
Conclusion
It is difficult to identify the knowledge and skills needed by UAS maintenance personnel, due to the ever changing advancements in technology and system design. It is clear however, that UAS maintenance personnel require a significantly different skill set to their counterparts in manned aviation. System components such as laptop computers, modems, and radio communication systems are critical to the safety of unmanned flight and present significant human factor issues. Future requirements or guidance for UAS maintenance training or qualifications must go beyond the traditional manned aviation maintenance programs and should include those topics associated with the advanced UAS technology.
References
Barnhart, Richard K., Shappee, Eric, and Marshall, Douglas M. (2011). Introduction to Unmanned Aircraft Systems. London, GBR: CRC Press, 2011. ProQuest ebrary. Web. 8 December 2015.
Cooke, Nancy J., Pringle, Heather, and Pedersen, Harry, eds. Human Factors of Remotely Operated Vehicles, Volume 7. Amsterdam, NLD: JAI Press, 2006. ProQuest ebrary. Web. 8 December 2015.
FAA Modernization and Reform Act of 2012, 112th Congress 2d Session, Report 112-381, Conference Report to accompany H.R. 658 Retrieved from http://www.gpo.gov/fdsys/pkg/CRPT-112hrpt381/pdf/CRPT-112hrpt381.pdf
FAA Notice N 8900.227 (2013) retrieved from http://www.faa.gov/documentlibrary/media/notice/n_8900.227.pdf
Hobbs, A. Ph.D., Herwitz, S. Ph.D. (2008) Maintenance Challenges of small Unmanned Aircraft Systems-a Human Factors Perspective, An Introductory Handbook retrieved from http://human-factors.arc.nasa.gov/publications/Maint_Chall_Small_Unman_Aircraft_Human_Factors_Persp.pdf
Johnson, W.B., Maddox, M.E (2007). A Model to Explain Human Factors in Aviation Maintenance Retrieved from http://www.skybrary.aero/bookshelf/books/1482.pdf
Roadmap (2012). NextGen UAS Research, Development and Demonstration Roadmap Version 1.0 March 15, 2012 retrieved from https://fas.org/irp/program/collect/uas-nextgen.pdf
Skybrary (2013). ICAO SHELL Model Retrieved from http://www.skybrary.aero/index.php/ICAO_SHELL_Model
USI, (2015) Building Safe sUAS Organizations course workbook Copyright 2015 The Unmanned Safety Institute
Williams, K.W (2004). A Summary of Unmanned Aircraft Accident/Incident Data: Human Factors Implications, Retrieved from http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.79.4150&rep=rep1&type=pdf
Human Factor Challenges Associated with Maintenance of Unmanned Aircraft Systems
Robert J. Winn
Embry-Riddle Aeronautical University-WW-ASCI 638
Abstract
The expeditious pace with which Unmanned Aircraft Systems (UAS) are being introduced into the National Airspace System (NAS) presents many challenges. In meeting these challenges, the Federal Aviation Administration (FAA) as mandated by congress in the FAA Modernization and Reform Act (FMRA) of 2012, was tasked to “develop a comprehensive plan to safely accelerate the integration of civil unmanned aircraft systems into the National Airspace System.” Once integration has been achieved, processes and procedures addressing continued airworthiness of UAS must be developed, achieved and understood in order to keep these systems, as well as the general public, property and the NAS safe. Unfortunately, due to the fast pace with which these unmanned systems have been introduced previously established maintenance programs applicable to manned aviation do not address those aspects particular to unmanned programs. The dissimilarities between manned and unmanned systems, have called attention to numerous Human Factor issues. This case study will introduce Human Factors that are associated with these systems, present accident data and the challenges associated with unmanned aircraft systems maintenance programs.
Keywords: airworthiness, human factors, maintenance, public, safety, unmanned aircraft system,
Human Factor Challenges Associated with Maintenance of Unmanned Aircraft Systems
The Federal Aviation Administration (FAA) as mandated by congress in the FAA Modernization and Reform Act (FMRA) of 2012 was tasked to “develop a comprehensive plan to safely accelerate the integration of civil unmanned aircraft systems into the National Airspace System.” Once integration has been achieved, processes and procedures addressing continued airworthiness of UAS must be developed, achieved and understood in order to keep these systems as well as the general public, property and the NAS safe. These processes and procedures will be addressed in regulations to ensure UAS are maintained in an airworthy condition.
The regulations must address the airworthiness of the UAV, qualifications of the operator (pilot), and any special operating rules when the UAV cannot meet the same requirements as manned aircraft (Cooke,2006). But the issue is that the regulations are developed after UAS integration into the NAS has already taken place.
The following section is taken directly from the FAAs Roadmap for UAS integration. It clearly shows that certification of UAS airframes is not on the radar until 2020/2030 and that research is still needed to support any regulations to ensure the continued airworthiness of the airframe /system.
3.2 Airframe Certification
Description of the challenge: Enable the rapid and affordable airframe certification for all types of UAS through increase emphasis on structural analysis and reduction in airframe testing. The existing basis of certification does not cover the new and novel materials and manufacturing processes being used in the manufacturing of UAS. As these methods and materials continue to evolve, research is needed to support an airworthiness determination and continue to ensure airworthiness over the life of the aircraft.
Goals:
Goal 1: Certify an airframe by analysis verified by test, 2020
Goal 2: Develop certification standards for advanced materials and structural design, 2020
Goal 3: Continued airworthiness through onboard health monitoring, 2030 (Roadmap, 2012).
Unfortunately, due to the fast pace with which these unmanned systems have been introduced to the general public, previously established manned maintenance programs do not address aspects significant to unmanned systems. The dissimilarities between manned and unmanned systems have called attention to numerous Human Factor issues. Human factors are a multidisciplinary approach to examining system design, training, experience, and individual motivation, with the objective of positively influencing human performance (USI, 2015). Two conceptual models used to analyze those human factor issues and for assessing and mitigating human factors in aviation maintenance are presented below.
SHEL
The original SHEL concept was developed using the first letters of each basic component, Software, Hardware, Environment and Liveware. The ICAO SHELL model (Fig. 1) introduced by Hawkins in 1975 illustrates how the concept is structured by conjoined blocks.
Source http://www.skybrary.aero/index.php/File:Liveware.jpg
This building block diagram is only intended as a basic aid to understanding Human Factors:
• Software - the rules, procedures, written documents etc., which are part of the standard operating procedures.
• Hardware - the Air Traffic Control suites, their configuration, controls and surfaces, displays and functional systems.
• Environment - the situation in which the L-H-S system must function, the social and economic climate as well as the natural environment.
• Liveware - the human beings - the controller with other controllers, flight crews, engineers and maintenance personnel, management and administration people - within in the system.
PEAR
In an article published in April 2007, Dr. William Johnson presented another conceptual model, where PEAR is used to recall four considerations for assessing and mitigating human factors in aviation maintenance:
• People who do the job; where Physical, Physiological, Psychological and Psychosocial factors are examined.
• Environment in which they work; considers the Physical and Organizational aspects
• Actions they perform; considers the WHAT (i.e. steps, performance, amount of people, communication [oral, visual, written] and information control requirements
• Resources necessary to complete the job. Considers procedures/work cards, Manuals/bulletins/FARs, Test equipment, Tools, Computers, paperwork /signoffs, Ground handling Equipment, Fixtures, materials, task lighting additional manpower and training.
Much like the building blocks in the SHELL model, the PEAR model provides basic factors to facilitate examination of a specific maintenance program. If those areas are weak or robust in nature they will be identified. This information is necessary to ensure that appropriate mitigations to correct them are implemented.
Hurdles
The Unmanned Safety Institute (USI) published a course workbook Building Safe sUAS Organizations (2015) which identified problems associated with UAS technology;
• The explosive number of systems available on the market combined with the relative low barriers to entry has attributed to UAS operations in the NAS as being crowded and dangerous.
• Many of the commercial UAS operators are amateurs turned “professional” and operate with complete ignorance of regulations and guidance.
• Even those who wish to comply with the regulations lack the aviation backgrounds and do not know where or how to begin.
• Those with manned aviation backgrounds find the unmanned systems challenging.
• Original Equipment Manufacturers are new to the aerospace industry and lack the ability to adapt to continued airworthiness requirements.
System Description
A description of a manned system is not very complicated. The aircraft or fuselage is the core component which facilitates the power supply/engine(s), fuel, communication/navigation equipment and provides a command and control platform for the pilot(s) free from external environmental distractions.
Unmanned systems are significantly different, in that the “system” consists of these primary separate components;
• Air vehicle
• Control station
• Payload
• Navigation Systems
• Communications –up/down data links
• Launch and Recovery equipment
• Operator/Pilot
UAS Incident Data
As with any new technology rushed to market, the UAS industry has been plagued by failures at a rate of approximately 1 in every 200 flying hours. These failures are directly related to lack of system standards, certification and poor maintenance oversight.
About 80% of maintenance mistakes in manned aviation involve human factors and if not detected would lead to accidents. Reports regarding unmanned aircraft (UA) accidents have been shown to be higher than that of manned aviation. In order to improve the safety of these systems identifying and understanding the factors involved must be accomplished. The most reliable source for UA accident data currently is the military. The military has a relatively long history of UA use and is diligent in accurately recording information pertaining to accidents/incidents (Williams, 2004).
Accident Data/Classification
The military takes a two-step approach in the classification of UA accidents. The first step takes a rather broad approach to identify those accidents that were attributed to Human factors (Liveware/People) or system component failure (hardware). Within this first step a “Maintenance” category is included to identify those accidents directly attributed to maintenance personnel. In the second step, those accidents classified as related to human factors were classified according to specific human factors issues that are commonly addressed in current research (Williams, 2004).
Data classification from the U.S Army Hunter program shows that accidents attributed to the Aircraft (hardware) accounted for 50% of the Hunter accidents. However, the data also shows that Human Factors and Maintenance errors combined for 56% of the programs accidents. Data, associated with U.S Air Force Predator failures attributes Maintenance (17%), Human Factors (67%) and Aircraft (42%) as the causal factors.
Knowledge
In the book, Introduction to Unmanned Aircraft Systems, by Barnhart, Shapee and Marshall (2011) it was presented that new UAS and their technologies do not fit neatly into the currently accepted training programs, programs that have been proven effective for manned operations. Additionally, these flight systems are being produced faster than the existing flight-training regime can react to them. To compound these training deficiencies, new technology systems that perform similar functions do not look alike and operator interactions with these systems often are completely different. A case could be made that these same issues, regarding the inability to keep up with rapid technological advances, associated with unmanned systems would also be realized by those responsible for the continued airworthiness and maintenance of these systems.
System Maintenance
Maintenance activities are classified into two categories, that of scheduled and unscheduled maintenance, each with its own challenges. Scheduled tasks include routine inspections, adjustments, and time replacements of components. Although the distinction between scheduled and unscheduled maintenance is widely used in the aviation industry, UAS operators do not tend to make a clear distinction between the two. This is partly because in the absence of maintenance procedures, virtually all maintenance tasks are unscheduled (Hobbs, 2008).
Scheduled
Scheduled or preventative maintenance is normally accomplished during a prescribed schedule, recommended by the system manufacturer and or developed by the operator. Conducting these inspections and performing the required maintenance tasks are essential to ensuring that those parts and or systems that have a life limit or known time between failure (TBF) rate are addressed. Scheduled tasks tend to be performed frequently and become familiar, routine activities for the technician. The routine nature of such tasks can increase the chances of absent-minded errors such as memory lapses (Hobbs, 2008).
Unscheduled
Unscheduled maintenance is just what it sounds like. It is a required action due to a mishap where damage was incurred by the system, or requires maintenance be performed to conduct an analysis and repair of a system or hardware failure. Fault identification and diagnosis can be a time-consuming part of UA maintenance, particularly when faults involve avionics or computer systems (Hobbs, 2008).
Due to the lack of manufacturing procedures and guidance unscheduled maintenance can impose undue stress on the mechanic or operator as the lack of a general understanding of the system or repair requirements can cause a significant delay in meeting operational (airtime)/customer induced expectations.
Maintenance Challenges
UAS maintenance is defined as any activity performed on the ground before or after flight to ensure the successful and safe operation of the system. Small UAS maintenance bears little similarity to conventional aviation maintenance as it is currently unregulated, and is rarely performed by personnel with formal maintenance qualifications. (Hobbs, 2008).
In July 2013, the FAA published Unmanned Aircraft Systems (UAS) Operational Approval Notice 8900.227 which stated that UAS Maintenance Qualifications, ratings and training requirements would be established as more data is collected and a regulatory guideline is developed. To date commercial sUAS operators are only required to make a self-certifying statement that the UAS will be maintained in an airworthy condition for operation in the NAS. However, no verification by the FAA is conducted to ensure that the operator has the training or knowledge to show an understanding of what “airworthy” means or that adequate inspection and maintenance procedures have been developed by the manufacturer or the operator to ensure the continued airworthiness of the system.
The bottom-line, the general public lacks the training and understanding that is required to ensure that an “aircraft” and its systems are in a condition for safe operation. This is even more of an issue due to proliferation of these systems available to the untrained public.
The complexity of these systems combined with relatively low reliability will translate into higher mishap rates and higher risk. It is therefore imperative that before and after every flight the system must be inspected for damage or malfunctioning equipment. It is equally important that the system is transported and stored in a safe and secure location (USI, 2015).
Conclusion
It is difficult to identify the knowledge and skills needed by UAS maintenance personnel, due to the ever changing advancements in technology and system design. It is clear however, that UAS maintenance personnel require a significantly different skill set to their counterparts in manned aviation. System components such as laptop computers, modems, and radio communication systems are critical to the safety of unmanned flight and present significant human factor issues. Future requirements or guidance for UAS maintenance training or qualifications must go beyond the traditional manned aviation maintenance programs and should include those topics associated with the advanced UAS technology.
References
Barnhart, Richard K., Shappee, Eric, and Marshall, Douglas M. (2011). Introduction to Unmanned Aircraft Systems. London, GBR: CRC Press, 2011. ProQuest ebrary. Web. 8 December 2015.
Cooke, Nancy J., Pringle, Heather, and Pedersen, Harry, eds. Human Factors of Remotely Operated Vehicles, Volume 7. Amsterdam, NLD: JAI Press, 2006. ProQuest ebrary. Web. 8 December 2015.
FAA Modernization and Reform Act of 2012, 112th Congress 2d Session, Report 112-381, Conference Report to accompany H.R. 658 Retrieved from http://www.gpo.gov/fdsys/pkg/CRPT-112hrpt381/pdf/CRPT-112hrpt381.pdf
FAA Notice N 8900.227 (2013) retrieved from http://www.faa.gov/documentlibrary/media/notice/n_8900.227.pdf
Hobbs, A. Ph.D., Herwitz, S. Ph.D. (2008) Maintenance Challenges of small Unmanned Aircraft Systems-a Human Factors Perspective, An Introductory Handbook retrieved from http://human-factors.arc.nasa.gov/publications/Maint_Chall_Small_Unman_Aircraft_Human_Factors_Persp.pdf
Johnson, W.B., Maddox, M.E (2007). A Model to Explain Human Factors in Aviation Maintenance Retrieved from http://www.skybrary.aero/bookshelf/books/1482.pdf
Roadmap (2012). NextGen UAS Research, Development and Demonstration Roadmap Version 1.0 March 15, 2012 retrieved from https://fas.org/irp/program/collect/uas-nextgen.pdf
Skybrary (2013). ICAO SHELL Model Retrieved from http://www.skybrary.aero/index.php/ICAO_SHELL_Model
USI, (2015) Building Safe sUAS Organizations course workbook Copyright 2015 The Unmanned Safety Institute
Williams, K.W (2004). A Summary of Unmanned Aircraft Accident/Incident Data: Human Factors Implications, Retrieved from http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.79.4150&rep=rep1&type=pdf
Sunday, December 6, 2015
7.6 IMPLEMENTING OPERATIONAL RISK MANAGEMENT
Running head: IMPLEMENTING OPERATIONAL RISK MANAGEMENT 1
Implementing Operational Risk Management to Improve
Small Unmanned Aircraft Systems (sUAS) Missions
Robert J. Winn
Embry-Riddle Aeronautical University-WW-ASCI638
Abstract
The unmanned aircraft system (UAS) industry has been growing at a significant rate. This growth has identified the need to establish risk assessment and hazard analysis mitigations to address unforeseen safety issues related to these systems and their operations. The UAS operational phase can be subdivide into several general stages: planning, staging, launch, flight, and recovery. Applying the appropriate hazard analysis tool within each stage will allow for early identification and ultimately early resolution of safety issues. This research paper will identify a small UAS (SUAS) that is currently in use in either the commercial or military sector and present an Operational Risk Management (ORM) assessment tool that can be used by the sUAS operators to safely assess their ability to accomplish the mission. This paper will also show the development of the ORM assessment tool by presenting a Preliminary Hazard List (PHL), a Preliminary Hazard Assessment (PHA) and the Operational Hazard Review and Analysis (OHR&A) and when used together provides sUAS operators the ability to safely integrate the National Airspace System (NAS).
Keyword: Analysis, Assessment, Hazard, Operations, Risk,
Implementing Operational Risk Management to Improve
Small Unmanned Aircraft Systems (sUAS) Missions
System safety is essential for both manned and unmanned systems when operating in the NAS. In a paper presented by Donald E. Gramp of the FAA, dated October 29, 2010, he stated:
“Small unmanned aircraft, as with other unmanned aircraft, are operated by a pilot physically separated from the aircraft. This renders the pilot incapable of conforming to the provisions of 14 CFR 91.113 with respect to seeing and avoiding other aircraft while operating in visual meteorological conditions. It also presents unique challenges in terms of maintaining the electronic connectivity essential to the safe operation and seamless integration of sUAS into the NAS. The hazard analysis included in this assessment reflects the implications of these attributes”.
The following hazards listed in order of greatest risk to the NAS are included in this assessment:
• Fly-away protection failure
• Loss of control
• Lost visual contact with UA
• Pilot/observer error
• Loss of voice communication with ATC
• Loss of voice communication (pilot/observer)
Thru hazard analysis, operators can potentially identify hazards associated with a particular phase or stage of the operation. A typical system safety task for hazard identification involves the preparation of a preliminary hazard list (PHL). This is accomplished by reviewing lessons learned, accident reports, and other historical data (Stephans, 2012). Having identified potential hazards, a subjective evaluation regarding probability, severity and exposure to those hazards is performed. The purpose of the evaluation is to determine the level of risk associated with the hazards; if it is deemed acceptable, if it can be eliminated, reduced or if the operation needs to be cancelled altogether. A robust risk management program (RMP) consists of three major parts: a hazard assessment, a prevention program and an emergency response program (Stephans, 2012).
For the benefit of this research paper, the AeroVironment Raven RQ-11B sUAS will be analyzed to identify potential hazards associated with a particular phase of its operation(s).
Raven
The Raven is the most widely used sUAS in the world. It can be hand launched and is controlled by a ground based operator either manually or preprogrammed for autonomous operation using advanced avionics and GPS navigation.
Preliminary Hazard list
The Preliminary Hazard List (PHL) is developed by individuals most familiar with the sUAS operation and a particular stage or phase of that operation. By brainstorming possible safety concerns associated with a stage or phase of operation, the PHL is created. The PHL tool (Fig.1) is instrumental in evaluating any one of the specific stages in the RAVENs operations (e.g. planning, staging, launching, flight and recovery). Once the hazards have been listed a determination as to the probability and severity of the hazards must be performed.
Probability/Severity
Probability is classified as frequent, probable, occasional, remote, or improbable. Severity is categorized as catastrophic, critical, marginal, or negligible (Barnhart, 2011). Once the hazards have been classified an initial risk level (RL) must be identified. Assessed risks are expressed as a Risk Assessment Code (RAC) which is a combination of one severity category and one probability level. For instance, if we determined that launching the RAVEN from a field that has trees nearby then a probability of impacting a tree would be classified as Probable and be rated a probability level “B” (reference Fig. 1) and the severity category described as Marginal would be rated a “3” (reference Fig. 2).
Figure 1-Probability matrix adapted from MIL-STD-882E
Department of Defense Standard Practice System Safety
Figure 2-Severity matrix adapted from MIL-STD-882E
Department of Defense Standard Practice System Safety
Risk Assessment Code
Assessed risks are expressed as a Risk Assessment Code (RAC) which is a combination of one severity category and one probability level. In our example our RAC is expressed as “3B”. Therefore, when used in conjunction with the risk assessment matrix (RAM) (Fig.3) found in MIL-STd-882E a risk level of Serious is determined.
Figure 3-Risk assessment matrix adapted from MIL-STD-882E
Department of Defense Standard Practice System Safety
Preliminary Hazard Analysis
The preliminary hazard analysis (PHA), allows us to determine ways to mitigate the previously identified hazards and initial risks. As depicted in Figure 4 a Raven staging and launch process is broken down into identified hazards, its probability of occurrence, the severity of risk, and mitigating actions. Using the RAC/RAM previously expressed of 3B/Serious we can determine that the Mitigation Action for Item S-3 is; “ensure clear launch flight path; issue launch warning.” And thereby the Resultant Risk Level (RRL) is classified as Medium downgraded from serious.
Figure 4-Preliminary Hazard List/Analysis adapted from EWOB dated July 16, 2014
Operational Hazard Review and Analysis
The Operational Hazards Review and Analysis tool (Fig. 5) is used to identify and evaluate hazards throughout the entire process or operations. The OHR&A is essential to ongoing hazards evaluation and provides the necessary feedback to assess the effectiveness of mitigating actions. Similar in form to the PHL/A, the different column in an OHR&A is the Action Review column which lists the mitigating actions identified in the PHL/A and determines if they were satisfactory (Barnhart, 2011).
Figure 5 Operational Hazards Review and Analysis retrieved from EWOB dated July 16, 2014
Operational Risk Management
Risk management activities are designed to assist the project manager and team members in understanding previously identified risks, the probability and consequences of failure and to identify and implement appropriate mitigations. As can be seen in Figure 6, Subtask 2 Implementation mitigations and those directly responsible for management of the activity are identified.
Figure 6-Organizational Risk Management Worksheet Retrieved from EWOB dated July 16, 2014.
References
AV-AeroVironment (2012, October). AeroVironment’s Puma All Environment (Ae) small Unmanned Aircraft System (sUAS), Puma AE White Paper, presented at the initial project safety review FAA/LA-ACO, Lakewood, CA.
Barnhart, Richard K., Shappee, Eric, and Marshall, Douglas M. Introduction to Unmanned Aircraft Systems. London, GBR: CRC Press, 2011. ProQuest ebrary. Web. 1 December 2015.
EWOB (2014) Managing Risks in sUAS Operations retrieved from http://lewob.blogspot.com/2014/07/managing-risks-in-suas-operations.html
Gramp, D.E. (2010) Small Unmanned Aircraft System (sUAS) Notice of Proposed Rulemaking Safety Risk Management Assessment Retrieved from https://avssp.faa.gov/avs/afs80/afs-86/Shared%20Documents/Small%20Unmanned%20Aircraft%20System%20(sUAS)%20Notice%20of%20Proposed%20Rule%20Making%20Safety%20Risk%20Management%20Assessment.pdf
Implementing Operational Risk Management to Improve
Small Unmanned Aircraft Systems (sUAS) Missions
Robert J. Winn
Embry-Riddle Aeronautical University-WW-ASCI638
Abstract
The unmanned aircraft system (UAS) industry has been growing at a significant rate. This growth has identified the need to establish risk assessment and hazard analysis mitigations to address unforeseen safety issues related to these systems and their operations. The UAS operational phase can be subdivide into several general stages: planning, staging, launch, flight, and recovery. Applying the appropriate hazard analysis tool within each stage will allow for early identification and ultimately early resolution of safety issues. This research paper will identify a small UAS (SUAS) that is currently in use in either the commercial or military sector and present an Operational Risk Management (ORM) assessment tool that can be used by the sUAS operators to safely assess their ability to accomplish the mission. This paper will also show the development of the ORM assessment tool by presenting a Preliminary Hazard List (PHL), a Preliminary Hazard Assessment (PHA) and the Operational Hazard Review and Analysis (OHR&A) and when used together provides sUAS operators the ability to safely integrate the National Airspace System (NAS).
Keyword: Analysis, Assessment, Hazard, Operations, Risk,
Implementing Operational Risk Management to Improve
Small Unmanned Aircraft Systems (sUAS) Missions
System safety is essential for both manned and unmanned systems when operating in the NAS. In a paper presented by Donald E. Gramp of the FAA, dated October 29, 2010, he stated:
“Small unmanned aircraft, as with other unmanned aircraft, are operated by a pilot physically separated from the aircraft. This renders the pilot incapable of conforming to the provisions of 14 CFR 91.113 with respect to seeing and avoiding other aircraft while operating in visual meteorological conditions. It also presents unique challenges in terms of maintaining the electronic connectivity essential to the safe operation and seamless integration of sUAS into the NAS. The hazard analysis included in this assessment reflects the implications of these attributes”.
The following hazards listed in order of greatest risk to the NAS are included in this assessment:
• Fly-away protection failure
• Loss of control
• Lost visual contact with UA
• Pilot/observer error
• Loss of voice communication with ATC
• Loss of voice communication (pilot/observer)
Thru hazard analysis, operators can potentially identify hazards associated with a particular phase or stage of the operation. A typical system safety task for hazard identification involves the preparation of a preliminary hazard list (PHL). This is accomplished by reviewing lessons learned, accident reports, and other historical data (Stephans, 2012). Having identified potential hazards, a subjective evaluation regarding probability, severity and exposure to those hazards is performed. The purpose of the evaluation is to determine the level of risk associated with the hazards; if it is deemed acceptable, if it can be eliminated, reduced or if the operation needs to be cancelled altogether. A robust risk management program (RMP) consists of three major parts: a hazard assessment, a prevention program and an emergency response program (Stephans, 2012).
For the benefit of this research paper, the AeroVironment Raven RQ-11B sUAS will be analyzed to identify potential hazards associated with a particular phase of its operation(s).
Raven
The Raven is the most widely used sUAS in the world. It can be hand launched and is controlled by a ground based operator either manually or preprogrammed for autonomous operation using advanced avionics and GPS navigation.
Preliminary Hazard list
The Preliminary Hazard List (PHL) is developed by individuals most familiar with the sUAS operation and a particular stage or phase of that operation. By brainstorming possible safety concerns associated with a stage or phase of operation, the PHL is created. The PHL tool (Fig.1) is instrumental in evaluating any one of the specific stages in the RAVENs operations (e.g. planning, staging, launching, flight and recovery). Once the hazards have been listed a determination as to the probability and severity of the hazards must be performed.
Probability/Severity
Probability is classified as frequent, probable, occasional, remote, or improbable. Severity is categorized as catastrophic, critical, marginal, or negligible (Barnhart, 2011). Once the hazards have been classified an initial risk level (RL) must be identified. Assessed risks are expressed as a Risk Assessment Code (RAC) which is a combination of one severity category and one probability level. For instance, if we determined that launching the RAVEN from a field that has trees nearby then a probability of impacting a tree would be classified as Probable and be rated a probability level “B” (reference Fig. 1) and the severity category described as Marginal would be rated a “3” (reference Fig. 2).
Figure 1-Probability matrix adapted from MIL-STD-882E
Department of Defense Standard Practice System Safety
Figure 2-Severity matrix adapted from MIL-STD-882E
Department of Defense Standard Practice System Safety
Risk Assessment Code
Assessed risks are expressed as a Risk Assessment Code (RAC) which is a combination of one severity category and one probability level. In our example our RAC is expressed as “3B”. Therefore, when used in conjunction with the risk assessment matrix (RAM) (Fig.3) found in MIL-STd-882E a risk level of Serious is determined.
Figure 3-Risk assessment matrix adapted from MIL-STD-882E
Department of Defense Standard Practice System Safety
Preliminary Hazard Analysis
The preliminary hazard analysis (PHA), allows us to determine ways to mitigate the previously identified hazards and initial risks. As depicted in Figure 4 a Raven staging and launch process is broken down into identified hazards, its probability of occurrence, the severity of risk, and mitigating actions. Using the RAC/RAM previously expressed of 3B/Serious we can determine that the Mitigation Action for Item S-3 is; “ensure clear launch flight path; issue launch warning.” And thereby the Resultant Risk Level (RRL) is classified as Medium downgraded from serious.
Figure 4-Preliminary Hazard List/Analysis adapted from EWOB dated July 16, 2014
Operational Hazard Review and Analysis
The Operational Hazards Review and Analysis tool (Fig. 5) is used to identify and evaluate hazards throughout the entire process or operations. The OHR&A is essential to ongoing hazards evaluation and provides the necessary feedback to assess the effectiveness of mitigating actions. Similar in form to the PHL/A, the different column in an OHR&A is the Action Review column which lists the mitigating actions identified in the PHL/A and determines if they were satisfactory (Barnhart, 2011).
Figure 5 Operational Hazards Review and Analysis retrieved from EWOB dated July 16, 2014
Operational Risk Management
Risk management activities are designed to assist the project manager and team members in understanding previously identified risks, the probability and consequences of failure and to identify and implement appropriate mitigations. As can be seen in Figure 6, Subtask 2 Implementation mitigations and those directly responsible for management of the activity are identified.
Figure 6-Organizational Risk Management Worksheet Retrieved from EWOB dated July 16, 2014.
References
AV-AeroVironment (2012, October). AeroVironment’s Puma All Environment (Ae) small Unmanned Aircraft System (sUAS), Puma AE White Paper, presented at the initial project safety review FAA/LA-ACO, Lakewood, CA.
Barnhart, Richard K., Shappee, Eric, and Marshall, Douglas M. Introduction to Unmanned Aircraft Systems. London, GBR: CRC Press, 2011. ProQuest ebrary. Web. 1 December 2015.
EWOB (2014) Managing Risks in sUAS Operations retrieved from http://lewob.blogspot.com/2014/07/managing-risks-in-suas-operations.html
Gramp, D.E. (2010) Small Unmanned Aircraft System (sUAS) Notice of Proposed Rulemaking Safety Risk Management Assessment Retrieved from https://avssp.faa.gov/avs/afs80/afs-86/Shared%20Documents/Small%20Unmanned%20Aircraft%20System%20(sUAS)%20Notice%20of%20Proposed%20Rule%20Making%20Safety%20Risk%20Management%20Assessment.pdf
Tuesday, November 24, 2015
6.6 A COMPARISON OF AUTOMATED TAKEOFF AND LANDING SYSTEMS
Running head: A COMPARISON OF AUTOMATED TAKEOFF AND LANDING SYSTEMS 1
A Comparison of Automated Takeoff and Landing Systems Among
Manned and Unmanned Aircraft
Robert J. Winn
Embry-Riddle Aeronautical University-WW-ASCI638
Abstract
Since the beginning of aviation, man has continued to develop and improve automated aircraft systems intended to reduce the liveware workload associated with conducting all phases of flight operations. With the increased proliferation of unmanned aircraft systems (UAS) operating in excess of 24 hours and the capabilities of transport aircraft to engage in long-duration flight operations the necessity to reduce the workload of UAS operating crews has become more prevalent. This paper will analyze an automated system that is in use by both manned and unmanned flight operations during critical phases of flight. The automated system will be described as it relates to both operations and the capabilities and limitations of the system will be presented as well as its overall effects on safe operations. In closing, recommendations regarding the level of automation for future variants of the system will be presented.
Keywords, automation level, liveware, operations, safety, workload, NextGen
A Comparison of Automated Takeoff and Landing Systems Among
Manned and Unmanned Aircraft
The Federal Aviation Administration’s NextGen system was developed to modernize how the National Airspace System (NAS) is utilized. In order to allow more aircraft to operate within closer proximity to one another the aviation industry must implement automation which controls takeoff, landing and even ground taxi.
However, these automation systems are complex, and still require human inputs, even if just for programming. Contrary to their intention, this can actually increase pilot and controller workload as systems must be learned, programmed and monitored at all times for both manned and unmanned aircraft (Cooke, Pringle, & Pedersen, 2007)
This paper will provide a basic description of one of these systems and identify two platforms with which it is used. Capabilities and limitations of the system will be presented, as well as its effects Operational Safety and any possible recommendations for future enhancements.
Automated Takeoff and Landing Systems (ATLS)
Recent advancements in technology have allowed the NAS to be accessed by both manned and unmanned aircraft systems (UAS). Automated takeoff and landing systems or ATLS reduces the workload of the Air traffic Controller and of the flight crew during the most critical phases of operations; takeoff, landing and ground taxi. Two distinctly different operating platforms incorporate ATLS to reduce the flight crew’s workload during these most critical phases of flight, these platforms are the UAS Northrop Grumman Global Hawk and the manned air transport Boeing 777.
Global Hawk
The Global Hawk is a long endurance UAS capable of 32 hours of operation. The flight crews are invariably assigned to rotating shifts in order to accommodate these long flight hours and are most likely subjected to fatigue issues brought about by interruptions to their natural circadian rhythms. In an attempt to minimize the workload of the flight crews during the phases of fatigue, the Global Hawk is configured with satellite and line of site (LOS) data link control capability via the ground control station (GCS). The satellite link provides critical Global Positioning System (GPS) navigation data to the Global Hawk. Combined with a synthetic aperture radar moving target indicator (SAR/MTI) a high resolution electro-optical (EO) digital camera and a third-generation infrared (IR) sensor, all operating through a common signal processor making it capable of fully autonomous takeoff, flight and landing (Northrup Grumman , 2012).
This critical flight navigation data is used by the Mission Control Element (MCE) via the GCS and enables the flight crew to monitor all sensors, perform mission planning and if necessary change the autonomous flight operation using manual inputs and control. For the ground portions of its flight missions, including autonomous takeoff, landing and taxi operations the Launch and Recovery unit Element, or LRE, is used. This is primarily accomplished with its Differential Global Positioning System (DGPS) and with its LOS connectivity and operation capabilities (Northrup Grumman , 2012).
By means of this autonomous system the Global Hawk is the epitome of long-endurance flight operations, still capable of liveware intervention.
Boeing 777
The Boeing 777 autonomous flight capabilities are in many ways similar to those of the Global Hawk and other UAV systems. The 777 is capable of autonomous takeoff, landing and flight, all with minimum pre-programming and inputs from flight crews (Boeing, 2014). In some aspects the infrastructure required for autonomous flight control of the 777 is not the same as that of the Global Hawk. Instead of a satellite and LOS command and control by means of the GCS the 777 takes advantage of its onboard flight crew and two primary autonomous systems; the Airplane Information Management System (AIMS) and the Electronic Flight Bag (EFB). By means of onboard sensors which provide critical system feedback of inflight controls and communication with ATC, the AIMS is capable of managing approach and departure procedures. The EFB minimizes crew workload for the majority of normal flight operations by automating checklists, flight plans and ATC approach information. By means of the EFB during the non-critical phase of operations the crew is less likely to have been subjected to workload fatigue and can focus more on the autonomous attributes of the ALTS during a flight critical phase.
Capabilities
By use of imploring autonomous control during critical phases of flight it removes the capabilities of error thru the liveware/hardware interface attributed to fatigue due to workload saturation.
Limitations
In any form, automation affects situational awareness by changing the operator’s role from actively controlling the system to passively monitoring the system (Endsley, 1996). When workload is reduced so is the operator’s situational awareness of the given task. To further compound task shredding via automation, should the automated task fail, the operator is less likely to successfully take control as the task has not been practiced and a complete understanding of the failure mode is unknown.
Without human input and intervention, the automated systems have no self-preservation motivations and can literally fly themselves into the ground, or follow unsafe inputs, simply because there is no reasoning of “this doesn't look right,” when an incorrect input or event is occurring in autonomous flight (Brown, 2015)
Operational Safety
The 777 ATLS are probably more likely to incur manual override than the Global Hawks as the crewmembers are one with the aircraft, not in a GCS, providing them with increased situational awareness. On the other hand, the Global Hawk pilot must rely on feedback from the UAV’s infrastructure to determine if there’s a problem that requires manual override. Using a fully autonomous system is designed to remove incorrect human pilot input errors that could cause unsafe flight conditions. However, as is illustrated in numerous manned and unmanned NTSB accident reports when autonomous systems were engaged, that is not entirely possible due to the human inputs necessary to program and design the autonomous software for flight ops in both manned and UAS systems (Cooke, Pringle, & Pedersen, 2007). Let’s not forget the adage, “A computer is only as smart as the operator”.
Training
Despite the incredible amount of automated flight capability in both unmanned and manned aircraft today, there is still a need for human insight and oversight to protect the machinery from itself when given faulty software or human inputs (Brown, 2015). To meet these challenges and to trust the capabilities the automated systems provide, those critical phases of flight must be part of simulator training so that the crews can recognize when automation is in error or has failed, allowing for manual control of the situation.
Level of Automation
Issues such as unbalanced workload, loss of SA, and skill loss can be addressed successfully by implementing Adaptive Automation (AA). Adaptive Automation is characterized by the ability to turn itself on in connection with a system or an operator event (Barnhart, 2011).
Current autonomous systems operate at a Level of Autonomy 1-3 (Low LoA) where the liveware (human) interface is the main component. As autonomous systems become more accepted by the liveware interface (operator) and user (passenger) these autonomous systems will progress in the near future to a level 7-9 (High LoA). At this level the system has very little interface with the liveware and no longer needs approval to execute its assigned operation/goal. The system will inform the human of its intent and will proceed unless there is human intervention.
Recommendation for Future Enhancements
Whereas AA is dynamic and flexible, traditional automation is static; total automation or autonomy is neither. At Beyond Level 10, autonomy or full automation proposes a strong artificial intelligence (AI) approach to automation. Humans have the unique ability to perform abstract judgment and reasoning tasks in undefined or ill-defined circumstances. So, it is unclear whether systems at a LoA 10 can be considered to be of human-level intelligence (Barnhart, 2011).
References
Barnhart, Richard K., Shappee, Eric, and Marshall, Douglas M.. Introduction to Unmanned Aircraft Systems. London, GBR: CRC Press, 2011. ProQuest ebrary. Web. 24 November 2015.
Brown, J. (2015) Automated Takeoff and Landing Systems in Manned and Unmanned Aircraft, Retrieved from http://www.droningonandon.com/blog/automated-takeoff-and-landing-systems-in-manned-and-unmanned-aircraft
Cooke, N., Pringle, H., & Pedersen, H. (2007). Human Factors of Remotely Operated Vehicles (Vol. 7). JAI Press.
Endsley, M. 1996. Automation and situation awareness, In Automation and Human Performance: Theory and Applications, ed. R. Parasuraman and M. Mouloua, 163– 181. Mahwah, NJ: Erlbaum.
Northrup Grumman . (2012, April ). Capabilities . Retrieved January 31, 2015, from http://www.northropgrumman.com/Capabilities/RQ4Block10GlobalHawk/Documents/GHMD-New-Brochure.pdf
Orlady, H.W., Orlady, L.M. (2012) Automation, Human factors in multi-crew flight operations (pg. 239) Location: Ashgate
A Comparison of Automated Takeoff and Landing Systems Among
Manned and Unmanned Aircraft
Robert J. Winn
Embry-Riddle Aeronautical University-WW-ASCI638
Abstract
Since the beginning of aviation, man has continued to develop and improve automated aircraft systems intended to reduce the liveware workload associated with conducting all phases of flight operations. With the increased proliferation of unmanned aircraft systems (UAS) operating in excess of 24 hours and the capabilities of transport aircraft to engage in long-duration flight operations the necessity to reduce the workload of UAS operating crews has become more prevalent. This paper will analyze an automated system that is in use by both manned and unmanned flight operations during critical phases of flight. The automated system will be described as it relates to both operations and the capabilities and limitations of the system will be presented as well as its overall effects on safe operations. In closing, recommendations regarding the level of automation for future variants of the system will be presented.
Keywords, automation level, liveware, operations, safety, workload, NextGen
A Comparison of Automated Takeoff and Landing Systems Among
Manned and Unmanned Aircraft
The Federal Aviation Administration’s NextGen system was developed to modernize how the National Airspace System (NAS) is utilized. In order to allow more aircraft to operate within closer proximity to one another the aviation industry must implement automation which controls takeoff, landing and even ground taxi.
However, these automation systems are complex, and still require human inputs, even if just for programming. Contrary to their intention, this can actually increase pilot and controller workload as systems must be learned, programmed and monitored at all times for both manned and unmanned aircraft (Cooke, Pringle, & Pedersen, 2007)
This paper will provide a basic description of one of these systems and identify two platforms with which it is used. Capabilities and limitations of the system will be presented, as well as its effects Operational Safety and any possible recommendations for future enhancements.
Automated Takeoff and Landing Systems (ATLS)
Recent advancements in technology have allowed the NAS to be accessed by both manned and unmanned aircraft systems (UAS). Automated takeoff and landing systems or ATLS reduces the workload of the Air traffic Controller and of the flight crew during the most critical phases of operations; takeoff, landing and ground taxi. Two distinctly different operating platforms incorporate ATLS to reduce the flight crew’s workload during these most critical phases of flight, these platforms are the UAS Northrop Grumman Global Hawk and the manned air transport Boeing 777.
Global Hawk
The Global Hawk is a long endurance UAS capable of 32 hours of operation. The flight crews are invariably assigned to rotating shifts in order to accommodate these long flight hours and are most likely subjected to fatigue issues brought about by interruptions to their natural circadian rhythms. In an attempt to minimize the workload of the flight crews during the phases of fatigue, the Global Hawk is configured with satellite and line of site (LOS) data link control capability via the ground control station (GCS). The satellite link provides critical Global Positioning System (GPS) navigation data to the Global Hawk. Combined with a synthetic aperture radar moving target indicator (SAR/MTI) a high resolution electro-optical (EO) digital camera and a third-generation infrared (IR) sensor, all operating through a common signal processor making it capable of fully autonomous takeoff, flight and landing (Northrup Grumman , 2012).
This critical flight navigation data is used by the Mission Control Element (MCE) via the GCS and enables the flight crew to monitor all sensors, perform mission planning and if necessary change the autonomous flight operation using manual inputs and control. For the ground portions of its flight missions, including autonomous takeoff, landing and taxi operations the Launch and Recovery unit Element, or LRE, is used. This is primarily accomplished with its Differential Global Positioning System (DGPS) and with its LOS connectivity and operation capabilities (Northrup Grumman , 2012).
By means of this autonomous system the Global Hawk is the epitome of long-endurance flight operations, still capable of liveware intervention.
Boeing 777
The Boeing 777 autonomous flight capabilities are in many ways similar to those of the Global Hawk and other UAV systems. The 777 is capable of autonomous takeoff, landing and flight, all with minimum pre-programming and inputs from flight crews (Boeing, 2014). In some aspects the infrastructure required for autonomous flight control of the 777 is not the same as that of the Global Hawk. Instead of a satellite and LOS command and control by means of the GCS the 777 takes advantage of its onboard flight crew and two primary autonomous systems; the Airplane Information Management System (AIMS) and the Electronic Flight Bag (EFB). By means of onboard sensors which provide critical system feedback of inflight controls and communication with ATC, the AIMS is capable of managing approach and departure procedures. The EFB minimizes crew workload for the majority of normal flight operations by automating checklists, flight plans and ATC approach information. By means of the EFB during the non-critical phase of operations the crew is less likely to have been subjected to workload fatigue and can focus more on the autonomous attributes of the ALTS during a flight critical phase.
Capabilities
By use of imploring autonomous control during critical phases of flight it removes the capabilities of error thru the liveware/hardware interface attributed to fatigue due to workload saturation.
Limitations
In any form, automation affects situational awareness by changing the operator’s role from actively controlling the system to passively monitoring the system (Endsley, 1996). When workload is reduced so is the operator’s situational awareness of the given task. To further compound task shredding via automation, should the automated task fail, the operator is less likely to successfully take control as the task has not been practiced and a complete understanding of the failure mode is unknown.
Without human input and intervention, the automated systems have no self-preservation motivations and can literally fly themselves into the ground, or follow unsafe inputs, simply because there is no reasoning of “this doesn't look right,” when an incorrect input or event is occurring in autonomous flight (Brown, 2015)
Operational Safety
The 777 ATLS are probably more likely to incur manual override than the Global Hawks as the crewmembers are one with the aircraft, not in a GCS, providing them with increased situational awareness. On the other hand, the Global Hawk pilot must rely on feedback from the UAV’s infrastructure to determine if there’s a problem that requires manual override. Using a fully autonomous system is designed to remove incorrect human pilot input errors that could cause unsafe flight conditions. However, as is illustrated in numerous manned and unmanned NTSB accident reports when autonomous systems were engaged, that is not entirely possible due to the human inputs necessary to program and design the autonomous software for flight ops in both manned and UAS systems (Cooke, Pringle, & Pedersen, 2007). Let’s not forget the adage, “A computer is only as smart as the operator”.
Training
Despite the incredible amount of automated flight capability in both unmanned and manned aircraft today, there is still a need for human insight and oversight to protect the machinery from itself when given faulty software or human inputs (Brown, 2015). To meet these challenges and to trust the capabilities the automated systems provide, those critical phases of flight must be part of simulator training so that the crews can recognize when automation is in error or has failed, allowing for manual control of the situation.
Level of Automation
Issues such as unbalanced workload, loss of SA, and skill loss can be addressed successfully by implementing Adaptive Automation (AA). Adaptive Automation is characterized by the ability to turn itself on in connection with a system or an operator event (Barnhart, 2011).
Current autonomous systems operate at a Level of Autonomy 1-3 (Low LoA) where the liveware (human) interface is the main component. As autonomous systems become more accepted by the liveware interface (operator) and user (passenger) these autonomous systems will progress in the near future to a level 7-9 (High LoA). At this level the system has very little interface with the liveware and no longer needs approval to execute its assigned operation/goal. The system will inform the human of its intent and will proceed unless there is human intervention.
Recommendation for Future Enhancements
Whereas AA is dynamic and flexible, traditional automation is static; total automation or autonomy is neither. At Beyond Level 10, autonomy or full automation proposes a strong artificial intelligence (AI) approach to automation. Humans have the unique ability to perform abstract judgment and reasoning tasks in undefined or ill-defined circumstances. So, it is unclear whether systems at a LoA 10 can be considered to be of human-level intelligence (Barnhart, 2011).
References
Barnhart, Richard K., Shappee, Eric, and Marshall, Douglas M.. Introduction to Unmanned Aircraft Systems. London, GBR: CRC Press, 2011. ProQuest ebrary. Web. 24 November 2015.
Brown, J. (2015) Automated Takeoff and Landing Systems in Manned and Unmanned Aircraft, Retrieved from http://www.droningonandon.com/blog/automated-takeoff-and-landing-systems-in-manned-and-unmanned-aircraft
Cooke, N., Pringle, H., & Pedersen, H. (2007). Human Factors of Remotely Operated Vehicles (Vol. 7). JAI Press.
Endsley, M. 1996. Automation and situation awareness, In Automation and Human Performance: Theory and Applications, ed. R. Parasuraman and M. Mouloua, 163– 181. Mahwah, NJ: Erlbaum.
Northrup Grumman . (2012, April ). Capabilities . Retrieved January 31, 2015, from http://www.northropgrumman.com/Capabilities/RQ4Block10GlobalHawk/Documents/GHMD-New-Brochure.pdf
Orlady, H.W., Orlady, L.M. (2012) Automation, Human factors in multi-crew flight operations (pg. 239) Location: Ashgate
Friday, November 20, 2015
5.4 AN ANALYSIS OF SHIFT SCHEDULE ROTATIONS
Running head: AN ANALYSIS OF SHIFT SCHEDULE ROTATIONS…………...……………1
An Analysis of Shift Schedule Rotations to allow for 24/7 UAS Operations
Conducted by 4 Teams
Robert J. Winn
Embry-Riddle Aeronautical University-WW-ASCI 638
Abstract
This research paper will present an analysis of a shift schedule for a MQ-1B Medium Altitude, Long Endurance (MALE) UAS squadron of the United States Air Force (USAF). The schedule, based on a 6 days on, 2 days off rotational format in order to accommodate missions conducted 24/7, 365 days a year providing armed, Intelligence, Surveillance, and Reconnaissance (ISR) to forces operating in country. In order to accomplish this mission, the UAS crews were divided into 4 teams and assigned a shift work schedule of 6 days on, 2 days off. Under this shift schedule crew members have reported extreme fatigue while conducting operations due to a lack of quality sleep. In order to optimize operations a revised shift schedule will be introduced in order to address the fatigue issue reported by the crews. In conclusion, an analysis of the current schedule will address the pros and cons compared to the revised shift schedule.
Keywords: fatigue, inadequate sleep, optimized operations, shift schedule,
An Analysis of Shift Schedule Rotations to allow for 24/7 UAS Operations
Conducted by 4 Teams
The introduction of long-endurance unmanned aircraft systems (UAS), such as the MQ-1 Predator and MQ-9 Reaper, has necessitated the routine implementation of shift work for United States Air Force (USAF) UAS crewmembers in order to provide the necessary around-the-clock staffing of ground control stations (Tvaryanas, 2008). A current 4 team shift schedule to accommodate 24/7, 365 days a year operations by MQ-1B USAF crews has introduced reports of increased fatigue attributed to inadequate sleep. The 2 cycle shift schedule requires 4 crews to alternate between 12 hour day (1st cycle) and night (2nd cycle) shifts by working 6 days on then two days off and then rotating to the alternate 12 cycle for the next 6/2 rotation.
A study by Barnes & Matz in 1998, found Army UAS operators preferred longer over shorter rotations because they perceived the longer rotations allowed for better situational awareness of the tactical environment (Tvaryanas, 2006). It could be that the longer rotation preferred by the crews was to that of the shift duration (12 hours) and not to the cycle of six days on. Another study showed that shift-working crewmembers in a Predator UAS squadron had significantly increased fatigue, emotional exhaustion, and burnout relative to traditional aircrew from another “high-demand, low-density” weapon system. The squadron work schedule was redesigned, but preferred shift work practices were not fully implemented because of manpower constraints and crewmember preferences (Tvaryanas, 2008).
Fatigue/Stress
Fatigue is a “State of diminished Physical or mental efficiency”. Fatigue can be triggered by previous perceived stress which may lead to impairment of performance and function (Kocalevent, 2011). The state of being fatigued has an effect on an individual’s capability to handle given levels of stress. The major causes of fatigue are; Sleep Loss, Work Schedule, Circadian Rhythm Disruptions, Recreational or Extracurricular Activity
Stress is a complex phenomenon brought about by the pressures that life or a given situation present. Factors that affect stress are Individual, Environmental and Occupational. The inability to socialize with family and community can exacerbate individual stressors, those stressors can compound issues attributed to increased fatigue brought about by diminished physical or mental efficiency. How an individual handles stress can have a direct effect on the individual’s ability to decompress, get restful sleep and recharge both the physical and mental state of being.
8 vs. 12
Numerous studies have concluded that for each hour past an 8 hour shift the risk and potential for error increased by one. These errors were also more likely to occur during a night shift where disruption of natural circadian rhythm occurs. In order to minimize the overall risk on a shift system we need to consider the number of successive night shifts, the length of the night shifts and the pro-vision of breaks within them (Tvaryanas, 2008). Additional studies found that a 12 hr. night shift that included frequent rest breaks might well prove safer than a shorter 8 hr. night shift with only a single, mid-shift break. Likewise, the length of the night shifts and the number of successive night shifts involved in a shift system will act in combination to determine the overall risk on that system (Folkard, 2003).
Work Cycle Duration
Shift worker fatigue has been described as a function of shift timing, length, frequency, and regularity as well as intrashift and intershift recovery opportunities (Tvaryanas, 2008). Shift workers experience a wide range of problems from acute disturbances of circadian rhythms and sleep to diminished family and social lives (Tvaryanas, 2008). If the number of successive night shifts is directly attributed to errors brought about by fatigue and circadian rhythm disruptions, than it would stand to reason the current 6 day on -2 day off cycle is not the optimal schedule for ensuring safe UAS operations. Therefore a revised shift schedule to accommodate the 4 UAS teams has been developed.
2-2/3-2/2-3 Rotating Shift Schedule | 24/7 Shift Coverage
The length of the night shifts and the number of successive night shifts involved in a shift system will act in combination to determine the overall risk on that system (Folkard, 2003). Implementing a 2-2/3-2/2-3 rotating shift schedule using 4 teams (crews) and 2 twelve-hour shifts to provide 24/7 coverage provides the individual crews with less exposure to prolonged 12 hour night shift rotations (Figure 1). Implemented over a 4-week cycle each team works 2 consecutive day shifts, followed by 2 days off, returning to work for 3 consecutive day shifts, followed by another 2 days off, then returning for another 2 consecutive day shifts, followed by 3 days off duty. The cycle then repeats itself but the crews are then assigned to the night shift for the same 2-2/3-2/2-3 cycle.
Figure 1. 2-2/3-2/2-3 rotating shift schedule Retrieved from http://www.bmscentral.com/learn-employee-scheduling/2-2-3-2-2-3-rotating-shift/
It should be considered that although the shift durations are in 12 hour increments a minimum of 15 minutes of overlap would be added by the outgoing dayshift crew in order to provide for a positive hand-off to the gaining night shift crew.
Pros • No employee works more than three consecutive days
• 3-day weekend every other weekend
• Taking 2 vacation days on one of the 2-day work week gives 7 days off
Cons • Could work up to 62 hours in one week
• Long shift length (12 hours)
• Requires an average of 2 overtime hours per employee per week
(BMS, 2015)
Conclusion
M.J Thorpy presented in the Journal of Family Practice, (V59, No.1, 2010), that there was a marked increase in the risk for incidents during working hours suggests that working more than 4 consecutive 12-hour night shifts should be avoided. Therefore, shift crews should be made aware that a potential exists for increased errors towards the end of a 12 hour shift. Shift schedules should rotate clockwise rather than counterclockwise manner as it has been found easier to change the sleep/wake cycle to a clockwise shift rotation, as this follows the natural adaptive pattern of delaying the sleep period. Additional ways to improve the sleep –wake cycle is to improve shift-work conditions, such as bright light exposure and appropriately timed naps.
Dr. D. Schroeder presented in a 2008 FAA Fatigue Management Symposium the following:
Summary
• No single shift rotation plan can entirely resolve the work and rest scheduling demands placed on individuals
• Discussion of specific advantages and risks difficult due to great diversity of flexible and irregular hours
• Given the variability of flexible hours, focus should be on the actual working hours of employees and the timing of their sleep
Recommendations
• Employ ergonomic principles of scheduling as possible
• Shift rotation time should be no less than 10 hrs
References
BMS, Business management Systems (2015), 2-2 3-2 2-3 Rotating Shift Schedule | 24/7 Shift Coverage Retrieved from http://www.bmscentral.com/learn-employee-scheduling/2-2-3-2-2-3-rotating-shift/
Kocalevent, R. D., Hinz, A., Brahler, E., Klapp, B. F., (2011) Determinants of fatigue and stress Research article from BMC Research notes 2011, 4:238 Retrieved from http://www.biomedcentral.com/1756-0500/4/238
Folkard, S., Tucker, P.T., (2003) Shift Work, Safety and productivity Retrieved from Department of Psychology, Swansea University, Swansea, Wales, United Kingdom Occupational Medicine (Impact Factor: 1.03). 04/2003; 53(2):95-101. DOI: 10.1093/occmed/kqg047
Schroeder, D. Ph.D., (2008) Sleep/Wake Cycles and Performance of ATC Operators Presented at the FAA Fatigue Management Symposium, June 17-19, 2008 Retrieved from http://www.faa.gov/about/office_org/headquarters_offices/avs/offices/afs/afs200/media/aviation_fatigue_symposium/SchroederAppComplete.pdf
Thorpy, M.J., (2010) Managing the patient with shift-work disorder, Supplement to the Journal of Family Practice, Vol 59, No 1., January 2010, Retrieved from http://media.mycme.com/documents/29/culpepper_2010_swd_suppl_7021.pdf
Tvaryanas, A.P., Lopez, N., Hickey, P., Daluz, C., Thompson, W. T., Caldwell, J.L. (2006) Effects of Shift Work and Sustained Operations: Operator Performance in Remotely Piloted Aircraft (OP-REPAIR) Retrieved from http://www.wpafb.af.mil/shared/media/document/afd-090121-043.pdf
Tvaryanas, A.P., Platte, W., Swigart, C., Colebank, J., Miller, N.L., (2008) A Resurvey of Shift Work-Related Fatigue in MQ-1 Predator Unmanned Aircraft System Crewmembers Retrieved from http://www.dtic.mil/get-tr-doc/pdf?AD=ADA477976
An Analysis of Shift Schedule Rotations to allow for 24/7 UAS Operations
Conducted by 4 Teams
Robert J. Winn
Embry-Riddle Aeronautical University-WW-ASCI 638
Abstract
This research paper will present an analysis of a shift schedule for a MQ-1B Medium Altitude, Long Endurance (MALE) UAS squadron of the United States Air Force (USAF). The schedule, based on a 6 days on, 2 days off rotational format in order to accommodate missions conducted 24/7, 365 days a year providing armed, Intelligence, Surveillance, and Reconnaissance (ISR) to forces operating in country. In order to accomplish this mission, the UAS crews were divided into 4 teams and assigned a shift work schedule of 6 days on, 2 days off. Under this shift schedule crew members have reported extreme fatigue while conducting operations due to a lack of quality sleep. In order to optimize operations a revised shift schedule will be introduced in order to address the fatigue issue reported by the crews. In conclusion, an analysis of the current schedule will address the pros and cons compared to the revised shift schedule.
Keywords: fatigue, inadequate sleep, optimized operations, shift schedule,
An Analysis of Shift Schedule Rotations to allow for 24/7 UAS Operations
Conducted by 4 Teams
The introduction of long-endurance unmanned aircraft systems (UAS), such as the MQ-1 Predator and MQ-9 Reaper, has necessitated the routine implementation of shift work for United States Air Force (USAF) UAS crewmembers in order to provide the necessary around-the-clock staffing of ground control stations (Tvaryanas, 2008). A current 4 team shift schedule to accommodate 24/7, 365 days a year operations by MQ-1B USAF crews has introduced reports of increased fatigue attributed to inadequate sleep. The 2 cycle shift schedule requires 4 crews to alternate between 12 hour day (1st cycle) and night (2nd cycle) shifts by working 6 days on then two days off and then rotating to the alternate 12 cycle for the next 6/2 rotation.
A study by Barnes & Matz in 1998, found Army UAS operators preferred longer over shorter rotations because they perceived the longer rotations allowed for better situational awareness of the tactical environment (Tvaryanas, 2006). It could be that the longer rotation preferred by the crews was to that of the shift duration (12 hours) and not to the cycle of six days on. Another study showed that shift-working crewmembers in a Predator UAS squadron had significantly increased fatigue, emotional exhaustion, and burnout relative to traditional aircrew from another “high-demand, low-density” weapon system. The squadron work schedule was redesigned, but preferred shift work practices were not fully implemented because of manpower constraints and crewmember preferences (Tvaryanas, 2008).
Fatigue/Stress
Fatigue is a “State of diminished Physical or mental efficiency”. Fatigue can be triggered by previous perceived stress which may lead to impairment of performance and function (Kocalevent, 2011). The state of being fatigued has an effect on an individual’s capability to handle given levels of stress. The major causes of fatigue are; Sleep Loss, Work Schedule, Circadian Rhythm Disruptions, Recreational or Extracurricular Activity
Stress is a complex phenomenon brought about by the pressures that life or a given situation present. Factors that affect stress are Individual, Environmental and Occupational. The inability to socialize with family and community can exacerbate individual stressors, those stressors can compound issues attributed to increased fatigue brought about by diminished physical or mental efficiency. How an individual handles stress can have a direct effect on the individual’s ability to decompress, get restful sleep and recharge both the physical and mental state of being.
8 vs. 12
Numerous studies have concluded that for each hour past an 8 hour shift the risk and potential for error increased by one. These errors were also more likely to occur during a night shift where disruption of natural circadian rhythm occurs. In order to minimize the overall risk on a shift system we need to consider the number of successive night shifts, the length of the night shifts and the pro-vision of breaks within them (Tvaryanas, 2008). Additional studies found that a 12 hr. night shift that included frequent rest breaks might well prove safer than a shorter 8 hr. night shift with only a single, mid-shift break. Likewise, the length of the night shifts and the number of successive night shifts involved in a shift system will act in combination to determine the overall risk on that system (Folkard, 2003).
Work Cycle Duration
Shift worker fatigue has been described as a function of shift timing, length, frequency, and regularity as well as intrashift and intershift recovery opportunities (Tvaryanas, 2008). Shift workers experience a wide range of problems from acute disturbances of circadian rhythms and sleep to diminished family and social lives (Tvaryanas, 2008). If the number of successive night shifts is directly attributed to errors brought about by fatigue and circadian rhythm disruptions, than it would stand to reason the current 6 day on -2 day off cycle is not the optimal schedule for ensuring safe UAS operations. Therefore a revised shift schedule to accommodate the 4 UAS teams has been developed.
2-2/3-2/2-3 Rotating Shift Schedule | 24/7 Shift Coverage
The length of the night shifts and the number of successive night shifts involved in a shift system will act in combination to determine the overall risk on that system (Folkard, 2003). Implementing a 2-2/3-2/2-3 rotating shift schedule using 4 teams (crews) and 2 twelve-hour shifts to provide 24/7 coverage provides the individual crews with less exposure to prolonged 12 hour night shift rotations (Figure 1). Implemented over a 4-week cycle each team works 2 consecutive day shifts, followed by 2 days off, returning to work for 3 consecutive day shifts, followed by another 2 days off, then returning for another 2 consecutive day shifts, followed by 3 days off duty. The cycle then repeats itself but the crews are then assigned to the night shift for the same 2-2/3-2/2-3 cycle.
Figure 1. 2-2/3-2/2-3 rotating shift schedule Retrieved from http://www.bmscentral.com/learn-employee-scheduling/2-2-3-2-2-3-rotating-shift/
It should be considered that although the shift durations are in 12 hour increments a minimum of 15 minutes of overlap would be added by the outgoing dayshift crew in order to provide for a positive hand-off to the gaining night shift crew.
Pros • No employee works more than three consecutive days
• 3-day weekend every other weekend
• Taking 2 vacation days on one of the 2-day work week gives 7 days off
Cons • Could work up to 62 hours in one week
• Long shift length (12 hours)
• Requires an average of 2 overtime hours per employee per week
(BMS, 2015)
Conclusion
M.J Thorpy presented in the Journal of Family Practice, (V59, No.1, 2010), that there was a marked increase in the risk for incidents during working hours suggests that working more than 4 consecutive 12-hour night shifts should be avoided. Therefore, shift crews should be made aware that a potential exists for increased errors towards the end of a 12 hour shift. Shift schedules should rotate clockwise rather than counterclockwise manner as it has been found easier to change the sleep/wake cycle to a clockwise shift rotation, as this follows the natural adaptive pattern of delaying the sleep period. Additional ways to improve the sleep –wake cycle is to improve shift-work conditions, such as bright light exposure and appropriately timed naps.
Dr. D. Schroeder presented in a 2008 FAA Fatigue Management Symposium the following:
Summary
• No single shift rotation plan can entirely resolve the work and rest scheduling demands placed on individuals
• Discussion of specific advantages and risks difficult due to great diversity of flexible and irregular hours
• Given the variability of flexible hours, focus should be on the actual working hours of employees and the timing of their sleep
Recommendations
• Employ ergonomic principles of scheduling as possible
• Shift rotation time should be no less than 10 hrs
References
BMS, Business management Systems (2015), 2-2 3-2 2-3 Rotating Shift Schedule | 24/7 Shift Coverage Retrieved from http://www.bmscentral.com/learn-employee-scheduling/2-2-3-2-2-3-rotating-shift/
Kocalevent, R. D., Hinz, A., Brahler, E., Klapp, B. F., (2011) Determinants of fatigue and stress Research article from BMC Research notes 2011, 4:238 Retrieved from http://www.biomedcentral.com/1756-0500/4/238
Folkard, S., Tucker, P.T., (2003) Shift Work, Safety and productivity Retrieved from Department of Psychology, Swansea University, Swansea, Wales, United Kingdom Occupational Medicine (Impact Factor: 1.03). 04/2003; 53(2):95-101. DOI: 10.1093/occmed/kqg047
Schroeder, D. Ph.D., (2008) Sleep/Wake Cycles and Performance of ATC Operators Presented at the FAA Fatigue Management Symposium, June 17-19, 2008 Retrieved from http://www.faa.gov/about/office_org/headquarters_offices/avs/offices/afs/afs200/media/aviation_fatigue_symposium/SchroederAppComplete.pdf
Thorpy, M.J., (2010) Managing the patient with shift-work disorder, Supplement to the Journal of Family Practice, Vol 59, No 1., January 2010, Retrieved from http://media.mycme.com/documents/29/culpepper_2010_swd_suppl_7021.pdf
Tvaryanas, A.P., Lopez, N., Hickey, P., Daluz, C., Thompson, W. T., Caldwell, J.L. (2006) Effects of Shift Work and Sustained Operations: Operator Performance in Remotely Piloted Aircraft (OP-REPAIR) Retrieved from http://www.wpafb.af.mil/shared/media/document/afd-090121-043.pdf
Tvaryanas, A.P., Platte, W., Swigart, C., Colebank, J., Miller, N.L., (2008) A Resurvey of Shift Work-Related Fatigue in MQ-1 Predator Unmanned Aircraft System Crewmembers Retrieved from http://www.dtic.mil/get-tr-doc/pdf?AD=ADA477976
4.6 INSITU SCANEAGLE-ESTABLISHING A PATH
Running head: INSITU SCANEAGLE-ESTABLISHING A PATH
Insitu ScanEagle-Establishing a path for UAS to operate Beyond Line of Sight (BLOS)
Robert J. Winn
Embry-Riddle Aeronautical University-WW-ASCI638
Abstract
This paper presents the attributes of the Insitu ScanEagle and how this unmanned aerial system (UAS) is equipped to conduct operations beyond line of sight (BLOS) of the operator. It will present the needed infrastructure to support the flight operations and identify the necessary support equipment, what additional personnel are required, their roles and what procedures are in place to ensure the UAS operates safely in the National Airspace System (NAS). A comparison between BLOS and line of sight (LOS) operations will be discussed to show the advantages and disadvantages of each of these methods and what unique human factors are associated with switching between each method of operation. In closing, the paper will identify a current operation or Pathfinder currently in the test phase, through joint participation with industry and the FAA that encourages the private use of a UAS while operating under BLOS capabilities.
Keywords: BLOS, support equipment, human factors, pathfinder, personnel, procedures
Insitu ScanEagle-Establishing a Path for UAS to Operate
Beyond Line of Sight (BLOS)
The Insitu ScanEagle, classified as a small unmanned aircraft system or sUAS has a max takeoff weight of <55 lbs. and is capable of operating beyond line of sight (BLOS). Due to its small environmental foot print the ScanEagle is nearly undetectable and can remain airborne for more than 24 hours with a service ceiling of 15,000 feet. Comprised of a video datalink in both analog and digitally encrypted feed and a Command and Control or C2 datalink that is both encrypted and non-encrypted its capable of delivering live video feeds allowing the operator to stay one step ahead of any situation. Infrastructure The System is comprised of four primary elements, 1) the UA 2) the Mark 4 ground launcher (trailer mounted, pneumatically actuated, expeditionary 3) Ground Control Station or GCS (point and click command enabling semiautonomous real time control) 4) SkyHook (runway independent cable recovery system, requires no nets) and 5) Operating Crew (by type certification consists of (1) Pilot and (1) ground crew member (aids in the launch and recovery operations). In addition to the primary system elements, the necessary support equipment to enable BLOS operations is the GPS satellite relay, the satellite data link and the satellite uplink vehicle. Not normally addressed as support equipment or part of the system, but an aspect of crew resource management (CRM) is the coordination/communication with Air Traffic Controllers that provide essential operator feedback regarding manned air operations or other obstacles within the vicinity of the UA, so that predetermined mitigations can be enacted upon. Line of Sight
Line of Sight (LOS) operations refers to the ability to provide command and control of the UA via direct up-link /down-link between the GCS and the UA. Operating under LOS offers advantages over BLOS by minimizing the infrastructure, such as satellite relay/data link support equipment, needed to perform C2 of the UA. However a disadvantage to operating under LOS is that the extended range capabilities of the UA are restricted, i.e. the UA cannot travel out of direct signal reception of the GCS uplink antennas or C2 and data downlink is affected.
Beyond Line of Sight
Beyond Line of Sight (BLOS) operations refer to UAS operations via a satellite link (GPS) that reaches “over the horizon”. This allows the operator to control the UA from considerably longer distances where a ground based-direct line of sight (LOS) datalink may be hindered by extending beyond the horizon or behind obstacles, such as mountains. A clear disadvantage is the additional infrastructure required to provide BLOS capability (e.g. Satellite relay, Satellite data link and the Satellite uplink vehicle).
Crew Resource Management-CRM
As stated in an ERAU-ASCI 638 presentation (2013), “Typically there is a delay of approximately 2 seconds from operator input to the controls to execution of commands by the aircraft; this makes takeoff and landing procedures difficult if not impossible due to the need to rapidly respond to changes during critical phases of flight. To work around this problem, there is usually a separate Launch and Recovery Element (LRE) crew and Mission Crew Element (MCE) that work together to accomplish the entire flight. Good CRM between these two elements is crucial to safe operations and involves many human factors issues that can cause problems if not executed properly. Precise coordination, timing, communication, and duplicated settings in the GCS are critical because a breakdown of any one of these factors can cause an accident or incident. Common procedures, checklists and training are essential components of successful BLOS operations.” To enhance CRM between the pilot (MCE) and ground crew (LRE) Insitu implemented robust GCS software referred to as I-MUSE.
I-MUSE
I-MUSE (Insitu Multiple UAS Software Environment): provides the interface between the pilot and the ScanEagle aircraft. The software capabilities directly enhance the pilot’s ability to multitask operational requirements. I-MUSE functionality includes: plan flights; launch aircraft; operate the aircraft in flight; monitor the aircraft and the data collection; and recover the aircraft. I-MUSE is factory-installed on all GCS and provides the pilot with situational awareness information via visual displays of terrain, obstacles, altitudes, etc. (similar to a manned aircraft flight deck). It also provides multiple checklists to perform pre-flight; post-flight; and emergency tasks. Finally, since I-MUSE is the mission planning interface, the pilot may load maps, elevation information, satellite imagery, etc., to assist with mission planning. Overlays are permitted in I-MUSE to alert the pilot of no fly zones and air traffic corridors (Murray, 2013).
Pathfinder
In collaboration with the Federal Aviation Administration, while conducting operations in New Mexico, Insitu (a Boeing subsidiary) launched the first sUAS to perform commercial BLOS operations within the continental United States (Insitu, 2015). This particular Pathfinder will provide necessary data to show the abilities of BLOS operations while the ScanEagle performs video inspections and analysis of predetermined sections of the BNSF railway.
References
Insitu, Inc. (2015) Insitu Unmanned Aircraft Conducts Railway Monitoring, Historic First Flight with BNSF Railway, Retrieved from http://www.prnewswire.com/news-releases/insitu-unmanned-aircraft-conducts-railway-monitoring-historic-first-flight-with-bnsf-railway-300167570.html
Murray, T., Eastwick, J., Evans, C. (2013) White Paper: System Safety Assessment for ScanEagle Type Certificate with limitations (Restricted Category) Date: May 17, 2013 Rev. 0.0
3.5 Research: UAS Integration in the NAS
Robert J Winn
Embry-Riddle Aeronautical University-WW-ASCI638
The FAA is developing a project called the Next Generation Air Transportation System (NextGen). What are the goals of NextGen, and how does it seek to improve future aviation operations in the NAS?
By changing from a ground-based radar system to satellite based GPS system, NextGen hopes to improve air commerce in the NAS by providing direct routes to destinations (saving time and operating costs), by reducing traffic delays, by increasing capacity and to allow air traffic controllers greater flexibility in managing aircraft operations with increased safety.
Where UAS/NAS integration is concerned, the ultimate goal is to enable a responsive, efficient, timely, coordinated multiagency research and development (R&D) effort that will enable the U.S. to realize fully the benefits of UAS operations in the NAS (Next, 2012).
To ensure this goal is realized a NextGen Unmanned Aircraft Systems Research, Development and Demonstration Roadmap was created. The development and demonstration objectives are intended to address the sense-and-avoid capability for UAS operating in any given density within the NAS. The Roadmap also takes into consideration that “achieving safe UAS integration depends on a complex set of regulatory, technical, economic, and political factors that must be addressed in an integrated and systematic fashion” (Next, 2012).
How do UAS fit into this vision for the future keeping in mind the research you have done on Detect, Sense, and Avoid requirements, and Lost Link scenarios?
In order for UAS to safely integrate the NAS, they will require advanced autonomous technology and standards to avoid other traffic and must mitigate the safety concern regarding loss of communications within the HMI.
Since UAS are unmanned, they have no capability to perform see and avoid mitigations currently required of manned operations. Therefore, some yet to be approved sensory equipment, radar, or operations under visual line of sight (VLOS) must be implemented for this regulatory requirement. The Government Accountability Office (GAO), reported in 2008 that “no technology had been identified as a suitable substitute for a person on board the aircraft in seeing and avoiding other aircraft. Additionally, UASs’ communications and control links are vulnerable to unintentional or intentional radio interference that can lead to loss of control of an aircraft and an accident.”
By 2020, manned aircraft will be required to incorporate continuously improved technologies such as Automated Dependent Surveillance-Broadcast (ADS-B) in order to comply with NextGen expectations. As the “payload-envelope” of this technology is reduced and its operating capabilities enhanced, it will contribute significantly to the ability of all manned and unmanned operations in the NAS.
What human factors issues or challenges do you foresee with the implementation of NextGen and the integration of UAS?
Loss-of Link (LOL) during UAS operation in the NAS is probably the most critical factor in the human –machine interface (HMI). Should LOL occur while the UAS is in flight the operator has no ability to implement an evasive maneuver should another aircraft enter into the operating vicinity of the UAS. A study conducted on behalf of ERAU students specifically focused the HMI of UASs and the vulnerabilities of a LOL scenario. The results conveyed four functional goals including: pre-mission building and entering the emergency return profile, updating the lost link profile, detecting lost link and responding to lost link (Kaste, 2012).
References
GAO-08-511, Unmanned Aircraft Systems: Federal Actions needed to Ensure safety and Expand Their Potential Uses within the National Airspace System, Published: May 15, 2008 Publicly released May 15, 2008 retrieved from http://www.gao.gov/cgi-bin/getrpt?GAO-08-511
Kaste, K.; Archer, J.; Neville, K.; Blickensderfer, B.; Luxion, S., "An analysis of FAA certification regulations and guidelines for evaluating the unmanned aircraft human-machine interface: Lost link," in Systems and Information Design Symposium (SIEDS), 2012 IEEE , vol., no., pp.150-155, 27-27 April 2012
doi: 10.1109/SIEDS.2012.6215149
Next Generation Air Transportation System, NextGen UAS Research, Development and Demonstration Roadmap Version 1.0, March 15, 2012 retrieved from https://fas.org/irp/program/collect/uas-nextgen.pdf
Robert J Winn
Embry-Riddle Aeronautical University-WW-ASCI638
The FAA is developing a project called the Next Generation Air Transportation System (NextGen). What are the goals of NextGen, and how does it seek to improve future aviation operations in the NAS?
By changing from a ground-based radar system to satellite based GPS system, NextGen hopes to improve air commerce in the NAS by providing direct routes to destinations (saving time and operating costs), by reducing traffic delays, by increasing capacity and to allow air traffic controllers greater flexibility in managing aircraft operations with increased safety.
Where UAS/NAS integration is concerned, the ultimate goal is to enable a responsive, efficient, timely, coordinated multiagency research and development (R&D) effort that will enable the U.S. to realize fully the benefits of UAS operations in the NAS (Next, 2012).
To ensure this goal is realized a NextGen Unmanned Aircraft Systems Research, Development and Demonstration Roadmap was created. The development and demonstration objectives are intended to address the sense-and-avoid capability for UAS operating in any given density within the NAS. The Roadmap also takes into consideration that “achieving safe UAS integration depends on a complex set of regulatory, technical, economic, and political factors that must be addressed in an integrated and systematic fashion” (Next, 2012).
How do UAS fit into this vision for the future keeping in mind the research you have done on Detect, Sense, and Avoid requirements, and Lost Link scenarios?
In order for UAS to safely integrate the NAS, they will require advanced autonomous technology and standards to avoid other traffic and must mitigate the safety concern regarding loss of communications within the HMI.
Since UAS are unmanned, they have no capability to perform see and avoid mitigations currently required of manned operations. Therefore, some yet to be approved sensory equipment, radar, or operations under visual line of sight (VLOS) must be implemented for this regulatory requirement. The Government Accountability Office (GAO), reported in 2008 that “no technology had been identified as a suitable substitute for a person on board the aircraft in seeing and avoiding other aircraft. Additionally, UASs’ communications and control links are vulnerable to unintentional or intentional radio interference that can lead to loss of control of an aircraft and an accident.”
By 2020, manned aircraft will be required to incorporate continuously improved technologies such as Automated Dependent Surveillance-Broadcast (ADS-B) in order to comply with NextGen expectations. As the “payload-envelope” of this technology is reduced and its operating capabilities enhanced, it will contribute significantly to the ability of all manned and unmanned operations in the NAS.
What human factors issues or challenges do you foresee with the implementation of NextGen and the integration of UAS?
Loss-of Link (LOL) during UAS operation in the NAS is probably the most critical factor in the human –machine interface (HMI). Should LOL occur while the UAS is in flight the operator has no ability to implement an evasive maneuver should another aircraft enter into the operating vicinity of the UAS. A study conducted on behalf of ERAU students specifically focused the HMI of UASs and the vulnerabilities of a LOL scenario. The results conveyed four functional goals including: pre-mission building and entering the emergency return profile, updating the lost link profile, detecting lost link and responding to lost link (Kaste, 2012).
References
GAO-08-511, Unmanned Aircraft Systems: Federal Actions needed to Ensure safety and Expand Their Potential Uses within the National Airspace System, Published: May 15, 2008 Publicly released May 15, 2008 retrieved from http://www.gao.gov/cgi-bin/getrpt?GAO-08-511
Kaste, K.; Archer, J.; Neville, K.; Blickensderfer, B.; Luxion, S., "An analysis of FAA certification regulations and guidelines for evaluating the unmanned aircraft human-machine interface: Lost link," in Systems and Information Design Symposium (SIEDS), 2012 IEEE , vol., no., pp.150-155, 27-27 April 2012
doi: 10.1109/SIEDS.2012.6215149
Next Generation Air Transportation System, NextGen UAS Research, Development and Demonstration Roadmap Version 1.0, March 15, 2012 retrieved from https://fas.org/irp/program/collect/uas-nextgen.pdf
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