Research Assignment: Operational Risk Management

Gabriel P. Riccio

ASCI 638 Human Factors in Unmanned Systems

Embry-Riddle Aeronautical University-Worldwide

23 February 2018

Operational Risk Management

Introduction

            The Federal Aviation Administration (FAA) has been working diligently over the past few years in an effort to efficiently integrate small Unmanned Aerial Systems (sUAS) into our country’s National Airspace System (NAS).  According to the FAA, they expect to see sUAS used in agricultural applications, research and development projects, academic uses, inspections of bridges, power lines, pipelines and antennas, reach and rescue operations, and environmental and wildlife monitoring (United States. Federal Aviation Administration [U.S. FAA], 2016).  With the growth of UAS operations, the FAA has taken notice of the unique risks associated with their operations; two areas of concern are “see and avoid” operations as well as the potential for “loss of positive control (U.S. FAA, 2016).  Therefore, the FAA expects operators of sUAS perform a preflight assessment which considers methods to mitigate risk associated with unmanned flight operations (Wackwitz & Boedecker, 2015).  An Operational Risk Management (ORM) assessment quantifies risks for the purpose of mitigation and control (Wackwitz & Boedecker, 2015).  The development of an ORM assessment includes a Preliminary Hazard List (PHL), Preliminary Hazard Analysis (PHA), and Operational Hazard Review and Analysis (OHR&A) (Safety Assessments, 2011).

sUAS Agricultural Crop Spraying

            As stated previously the FAA is expecting and it has come to be true in all cases that sUAS are being used across a variety of applications; one of which is for the agricultural spraying of crops.  The small unmanned octocopter Agras MG-1 built by DJI is designed to precisely apply liquid pesticides, fertilizers, and herbicides (DJI, 2018).  This sUAS can spray up to 22 pounds of payload and spray seven to ten acres per hour (DJI, 2018).  The platform utilizes an intelligent spraying system that regulates payload application so as to reduce over-spraying thus protecting the environment while cutting operating costs (DJI, 2018).  The Agras MG-1 is a high-tech state of the art platform but it is imperative the commercial operator prior to flight develop an ORM assessment tool for the purpose of managing the safety of operations and aid in the “go/no-go decision” making process (Safety Assessments, 2011).

ORM Assessment Tool

            The first step in developing an ORM assessment tool is the development of a PHL.  The purpose of the PHL is to identify the initial safety issues associated with operations (Safety Assessments, 2011).  Once the risks have been identified, they need to be analyzed for the sole purpose of developing strategies to mitigate that particular risk/hazard (Safety Assessments, 2011).  In the development of the PHL; probability, severity, and risk are defined per “MIL-STD-882D/E Department of Defense Standard Practice System Safety” dated 11 May 2012.  See Tables 1, 2, and 3 below. See Table 4 for completed PHL/A table.

Table 1

   DOD severity categories.

Note:  Reprinted from Standard practice for system safety (MIL-STD-882E), U.S. DOD, 2012.

Table 2

 DOD probability levels.

Note:  Reprinted from Standard practice for system safety (MIL-STD-882E), U.S.  DOD, 2012.

Table 3

DOD risk level matrix.

Note:  Reprinted from Standard practice for system safety (MIL-STD-882E), U.S. DOD, 2012.

Table 4

PHL and PHA assessment.

Preliminary Hazard List/Analysis
Track#	Operational Stage	Hazard	Probability	Severity	RL	Mitigating Actions	RRL	Notes
001	Planning	Weather	Frequent	Marginal	Serious	Obtain a weather briefing	LOW	Continue to monitor
002	Planning	Airspace Violation	Improbable	Marginal	Medium	Operate IAW FAA/COA	LOW	Review airspace rules
003	Planning	Human Factors	Occasional	Marginal	Medium	Self-evaluate	LOW	Fatigue, Stress
004	Staging	Improper Pre-flight	Improbable	Marginal	Medium	Pre-flight IAW operators manual	LOW
005	Launch	Obstacles	Frequent	Marginal	Serious	Choose alternate launch location	LOW	Check for towers, wires, tree, etc.
006	Flight	Loss of Control	Remote	Marginal	Medium	Follow operating procedures	LOW	Check antennas
007	Fight	Loss of visual sight	Remote	Critical	Medium	Execute Lost Link Procedures	LOW	Use observer
008	Flight	Collision with other aircraft	Improbable	Critical	Medium	Operate IAW FAA/COA	LOW
009	Flight	Spray Drift	Remote	Marginal	Medium	Weather, winds, equipment	LOW	Update winds
010	Flight	Spray Off Target Damage	Improbable	Marginal	Medium	Pre-flight, Monitor Flight	LOW
011	Recovery	Improper Post-Flight	Improbable	Negligible	LOW	Post-Flight IAW operators manual	LOW
RL (Risk Level), RRL (Residual Risk Level)

The third step is to perform an OHR&A.  The OHR&A is used to evaluate the hazards that were not foreseen during operations from beginning to end; additionally, the OHR&A will validate the PHL and the PHA (Safety Assessments, 2011). See Table 5 below.

 Table 5

OHR&A tool.

Operational Hazard Review & Analysis (OHR&A)
Track#	Operational Stage	Action Review	Probability	Severity	RL	Mitigating Actions	RRL	Notes
001	Planning	Not Adequate	Occasional	Marginal	Medium	Update weather during flight operations	LOW	Constantly monitor
002	Planning	Adequate	Improbable	Marginal	Medium	Operate IAW FAA/COA	LOW
003	Planning	Not Adequate	Occasional	Marginal	Medium	Ensure operator is fully pre-pared and trained	LOW	USE FAA IMSAFE acronym
004	Staging	Adequate	Improbable	Marginal	Medium	Pre-flight IAW operators manual	LOW
005	Launch	Adequate	Frequent	Marginal	Serious	Choose alternated launch location	LOW
006	Flight	Adequate	Remote	Marginal	Medium	Follow operating procedures	LOW
007	Flight	Not Adequate	Occasional	Critical	Serious	Additional operator training	LOW	Strategically position observers
008	Flight	Adequate	Improbable	Critical	Medium	Operate IAWS FA/COA	LOW
009	Flight	Not Adequate	Remote	Marginal	Medium	Monitor Winds	LOW	Weather updates
010	Flight	Adequate	Improbable	Marginal	Medium	Pre-flight, Monitor Flight	Low
011	Recovery	Adequate	Improbable	Negligible	Low	Post-Flight IAW operators manual	LOW
RL (Risk Level), RRL (Residual Risk Level)

            The last step is the development of the ORM assessment tool.  The tool should be filled out prior to every flight and briefed to all mission participants (Safety Assessments, 2011). ORM factors should include the weather, human factors (crew rest, mission timeline), airspace, and any items on the PHL/A that may change for that particular mission (Safety Assessments, 2011). See Table 6 below.

Table 6

ORM assessment tool.

ORM Assessment Tool DJI Agras MG-1 Spraying Operations
Operational Factors	Risk Factor 1	Risk Factor 2	Risk Factor 3	Risk Factor 4
System Hardware/Software changes			YES
Battery Charge	100%	100% - 75%	75% - 50%	< 50% NF
Airspace Operations	Uncontrolled		Controlled
Pilot’s Last Flight	< 30 days	30 - 60 days	60 - 90 days	> 90 days
Visibility	> 5 miles	5 - 3 miles	3 - 1 mile	< 1 mile NF
Ceiling AGL	> 5,000’	5,000 – 3,000’	3,000’ – 1,000’	<1,000’
Surface Winds	Calm	0-10 Knots	10-15 Knots	> 15 Knots NF
Crew Rest	> 12 hours	12 - 8 hours	8 – 6 hours	< 6 hours NF
Previously Sprayed Current Location	< 30 days	30 - 60 days	60 - 90 days	> 90 days
Obstacles >150’	>  100 yards	100 – 75 yards	50 – 75 yards	< 50 yards
Note: NF (No Flight is Permitted)
Risk Level			TOTAL
< 6 is LOW	6 – 10 is Medium	>  10 is High

References

DJI. (2018). AGRAS MG-1. Retrieved from https://www.dji.com/mg-1

Safety Assessments. (2011). In R. K. Barnhart, S. B. Hottman, D. M. Marshall, & E. Shappee (Eds.), Introduction to unmanned aircraft systems (pp. 123-135). Retrieved from https://ebookcentral-proquest-com.ezproxy.libproxy.db.erau.edu/lib/erau/reader.action?docID=1449438&query=

United States. Department of Defense. (2012). Standard practice for system safety (MIL-STD-882E). Retrieved from website: https://www.system-safety.org/Documents/MIL-STD-882E.pdf

United States. Federal Aviation Administration. (2016). Operation and certification of small unmanned aircraft systems (RIN 2120–AJ60). Retrieved from https://www.faa.gov/uas/media/RIN_2120-AJ60_Clean_Signed.pdf

Wackwitz, K., & Boedecker, H. (2015, November). Safety risk assessment for UAV operation. Retrieved from http://miningquiz.com/pdf/Drone_Safety/Safety-Risk-Assessment-for-UAV-Operation-Rev.-1.1.compressed.pdf

           

Research Assignment: Automatic Takeoff and Landing

Gabriel P. Riccio

ASCI 638 Human Factors in Unmanned Systems

Embry-Riddle Aeronautical University-Worldwide

16 February 2018  

      

Automatic Takeoff and Landing

Introduction

            Many aerial platforms have some level of autopilot and autonomous functions.  Autopilots can significantly reduce pilot workload, especially during critical phases of flight such as during takeoff and landing (United States. Federal Aviation Administration [U.S. FAA], 2009).  Autopilots allow for the automatic control of the air vehicle, including altitude, climbs, descents, turns, headings, course interceptions, as well as navigating to waypoints (U.S. FAA, 2009).  Autopilot systems can be found on both manned and unmanned aircraft systems, the levels of automatic behaviors are dependent on the onboard specific avionics package as per platform design.  Autopilot systems are dependent on onboard sensors that provide information and data to the air vehicle’s autopilot system (Nasr, 2015).  Whether the platform has an onboard pilot or the pilot is remotely flying the unmanned aerial system (UAS) from a Ground Control Station (GCS) it is imperative that the human-in-the-loop understand the systems automation and automatic behaviors; there can be no confusion or misunderstanding on system operations (Nasr, 2015).

MQ-9 Reaper

            The MQ-9 Reaper is a military UAS designed to find, track, and destroy targets (Beno & Adamcik Jr., 2014). The Reaper is designed with a sophisticated autopilot and management flight system that enables the platform to operate with full autonomy (Beno & Adamcik Jr., 2014).  The UAS can takeoff, fly an entire mission, and automatically land without any human direct control intervention (Beno & Adamcik Jr., 2014).  The pilot has the authority and capability to take control of the platform at any time via the GCS for any reason during autonomous operations (Beno & Adamcik Jr., 2014).  An Air Force officer remarked that the ability of the Reaper to auto takeoff and land would make training easier for pilots and reduce the total amount of training time (Drew, 2016).  Research indicates that human factors errors are responsible for a significant percentage of UAS accidents, especially during takeoff and landing operations (Williams, 2004).  Therefore, equipping the Reaper with automatic takeoff and landing technology may very well mitigate the risks associated with these critical operations.  However, the advantage of automatic takeoff and landing is a disadvantage.  If a UAS Reaper pilot continually relies on the autopilot’s functions, they will most likely not be proficient at manual takeoff and landing operations when needed (Estes III, 2015).

Boeing 737

            Many commercial airliners are equipped with state of the art autopilots but they are still limited.  Prior to takeoff, the pilot is responsible to enter the route and other pertinent information for the flight so the autopilot can perform its duties (Nasr, 2015).  However, at this time the autopilot cannot ground taxi or perform an auto takeoff but autoland is a capability on some manned aircraft; such as the Boeing 737 (Nasr, 2015).  The Boeing 737 has autoland technology but there are limitations (FlightDeckFriend.com, n.d.).  The autoland feature is used during times of low visibility and low winds; the Boeing 737 autoland feature is limited to a 25-knot max crosswind (FlightDeckFriend.com, n.d).  Pilots of autoland aircraft require retraining every 6 months (FlightDeckFriend.com, n.d).  Additionally, the pilots must still correctly configure the aircraft for autoland and are responsible for speed control (FlightDeckFriend.com, n.d).

            FAA Advisory Circular 25.1329-1C titled “Approval of Flight Guidance Systems” addresses manned aircraft autopilot systems.  The advisory circular is very specific about the requirements for aircraft and pilot requirements in respect to autopilot systems and recognizes the importance of human factors, along with the aspects of the human-machine interface (U.S. FAA, 2014).  The Boeing 737 and its aircrew must meet all of the requirements of this advisory circular; some examples include autopilot switch functions, autopilot override, design of the controls, indicators, alerts, and knob shape and position (U.S. FAA, 2014).  The circular also specifies the requirements for an aircraft that wants to engage the autopilot below 500 feet after takeoff (U.S. FAA, 2014).

Conclusion

            The MQ-9 Reaper and Boeing 737 are both equipped with autopilot systems.  In the event of an emergency or any problem with the autopilot, the aircrews of either platform can take manual control.  The Boeing 737 does not have an auto takeoff function and perhaps does not require one at this time.  Since the aircraft is manned, the pilots can best maintain situational awareness by performing the takeoff themselves.  There is no significant advantage with an autopilot takeoff.  Commercial airliners manually land the aircraft nearly 100 percent of the time unless conditions dictate otherwise; pilots cite the demanding requirements of ensuring the automation is working as designed during an autoland as opposed to the ease of manual flying as the predominate reason (FlightDeckFriend.com, n.d).  It is somewhat ironic that UAS landings are better achieved with automation.  Taking the pilot out of the cockpit necessitates the need for autopilot capabilities to reduce UAS accidents as a result of human factors errors.

            The Reaper is already fully autonomous, the only improvements that could be made to this UAS system are improvements to the GCS.  A list of GCS improvements, especially if the pilot has to manually takeoff or land includes better sensory cues, improved visuals, simplify screen data during critical phases of flight, improve pilot control station ergonomics, and increase visual field of view (Shively, 2015).  The Boeing 737 is currently equipped with one of the most sophisticated autopilot systems.  One novel improvement to the autoland function that would reduce the human factors associated with the pilots having to monitor the automation and correctly configure the aircraft is to have a robot replace the co-pilot and control the aircraft’s autopilot functions. Sponsored by DARPA; Aurora Flight Science has successfully configured a robotic arm in a Boeing 737 flight simulator that was able to fly and land the aircraft (Szondy, 2017).  The robotic arm is a human factors improvement for the cockpit which would reduce pilot workload and improve decision making during stressful and distracting situations.  The robotic arm may very well be the technology needed to achieve auto takeoff for the Boeing 737 and similar aircraft.               

References

Beno, V., & Adamcik Jr., F. (2014, May). Unmanned combat air vehicle: MQ-9 Reaper. Paper presented at International Conference of Scientific Paper, Brasov, Romania. Retrieved from http://www.afahc.ro/ro/afases/2014/forte/BENO.pdf

Drew, J. (2016, May 4). USAF to automate MQ-9 takeoffs and landings. Retrieved from https://www.flightglobal.com/news/articles/usaf-to-automate-mq-9-takeoffs-and-landings-424975/

Estes III, A. S. (2015, February 16). Automatic takeoff and landing systems [Web log post]. Retrieved from https://knghthwksuas.weebly.com/uas-blogs/-automatic-takeoff-and-landing-systems

FlightDeckFriend.com. (n.d.). Can a plane land automatically?. Retrieved from https://www.flightdeckfriend.com/can-a-plane-land-automatically

Nasr, R. (2015, March 26). Autopilot: What the system can and can't do. Retrieved from https://www.cnbc.com/2015/03/26/autopilot-what-the-system-can-and-cant-do.html

Shively, J. (2015, March). Human performance issues in remotely piloted aircraft systems. ICAO: Remotely piloted or piloted: sharing one aerospace system. Symposium conducted at ICAO Headquarters, Montreal, Canada. Retrieved from https://ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa.gov/20160001869.pdf

Szondy, D. (2017, May 17). DARPA robot lands (simulated) Boeing 737 [Web log post]. Retrieved from https://newatlas.com/darpa-robot-boeing-737-landing-simulator/49580/

United States. Federal Aviation Administration. (2014). Approval of flight guidance systems (AC 25.1329-1C). Retrieved from Federal Aviation Administration website: https://www.faa.gov/regulations_policies/advisory_circulars/index.cfm/go/document.information/documentid/1026174

United States. Federal Aviation Administration. (2009). Advanced avionics handbook: FAA-H-8083-6. Retrieved from website: https://www.faa.gov/regulations_policies/handbooks_manuals/aviation/advanced_avionics_handbook/media/FAA-H-8083-6.pdf

Williams, K. W. (2004). A summary of unmanned aircraft accident/incident data: Human factors implications (DOT/FAA/AM-04/24). Washington, DC: U.S. Dept. of Transportation, Federal Aviation Administration, Office of Aerospace Medicine. Retrieved from www.dtic.mil/cgi-bin/GetTRDoc?AD=ADA460102

           

Research Assignment: Shift Work Schedule

Gabriel P. Riccio

ASCI 638 Human Factors in Unmanned Systems

Embry-Riddle Aeronautical University-Worldwide

7 February 2018 

Research Assignment: Shift Work Schedule

Introduction

            The United States Air Force (USAF) operates Unmanned Aerial Systems (UAS) around the clock in support of our nation’s defense.  USAF UAS squadrons are required to operate 24 hours a day and 365 days a year in support of “intelligence, surveillance, and reconnaissance” missions (Embry-Riddle Aeronautical University, n.d.).  There are concerns by the MQ-1B Squadron commander that their UAS crews are suffering from inadequate sleep and extreme fatigue while conducting operations.

            A study conducted by the USAF 311^th Human Systems Wing in 2006 evaluated the effects of shift work and prolonged operations on MQ-1 Predator UAS air-crews (Thompson, Lopez, DaLuz, & Caldwell, 2006).  The researchers’ concluded that a high percentage of UAS crews suffer from Shift Work Sleep Disorder (SWSD), increased fatigue, mental and emotional exhaustion, burnout, and a decrement in job performance with reduced alertness (Thompson et al., 2006).

            SWSD is a result of workers whose job requires them to function outside of the normal bodies desire to be asleep and awake (Drake, 2010).  SWSD can severally degrade a person’s ability to effectively function which could result in occupational accidents (Culepper, 2010).  Additionally, SWSD affects a person’s ability to sleep, eat, and increases stress (Culepper, 2010).

            A follow-up study to the 2006 USAF 311^th Human Systems Wing funded by the USAF 311^th Performance Enhancement Directorate examined the results of UAS crewmembers who used a “modified rotational work schedule” (Tvaryanas, Platte, Swigart, Colebank, J., & Miller, 2008).  In this follow up study, it is important to note that the air-crew work schedule was re-designed but not fully implemented due to a lack of personnel and personal work schedule preferences (Tvaryanas et al., 2008).  The results of the re-survey still indicated issues of chronic fatigue, lack of alertness, job-related stress, and exhaustion (Tvaryanas et al., 2008).  Prior to the survey, the researchers expected a decrease in fatigue and its associated complications due to a change in the work rotational schedule from weekly to monthly and one additional day off between shifts (Tvaryanas et al., 2008).  The researchers’ summarized that several factors may have influenced the survey results but the lack of personnel and the inability to fully implement the modified work schedule may have had the largest negative impact on the survey (Tvaryanas et al., 2008).

Current Shift Rotation

            The current shift rotation consists of four teams that work six days on, two days off; then rotate to the next shift.  This schedule is fatiguing and stressing out the crewmembers, which can potentially degrade their performance.  It must be noted that there are two positives that are associated with the current rotation.  Firstly, it is recommended by some researchers that the shift rotate on a morning –evening - night clockwise direction (which this shift currently does) as opposed to night – evening - morning counterclockwise direction (Thorpy, 2010).  Secondly, it is recommended that workers not be scheduled to work shifts greater than twelve hours; the current rotation is less than twelve (Thorpy, 2010).

Recommended Solution

            As stated previously, the current shift rotates in a clockwise direction and shifts are less than twelve hours long; these are two pluses which will be the starting point for a recommended shift schedule with the purpose of improving the reported fatigue issues.  Without giving any consideration to individual situational differences at this time concerning the worker’s ability to adapt to shift work, the DuPont shift rotation is recommended (Tvaryanas et al., 2008).

DuPont 24/7 Shift Rotation

            The “DuPont” work shift schedule rotation will keep the same four teams as in the current rotation but the work day will be based on a twelve-hour shift; this schedule is currently used by many police departments and factories (Business Management Systems, n.d.).  The advantages of a twelve-hour shift with four teams equates to more consecutive time off which should reduce aircrew fatigue.  Under the current rotation the crewmembers only have a maximum of two consecutive days off; under the DuPont rotation crew members get a combination of 1day, 3 days, and seven days off in a 28-day cycle (Business Management Systems, n.d.).  Since the shift rotates from day to night and night to day it avoids the problems associated with a counterclockwise rotation schedule because there is no swing shift.  Additionally, the shifts are no longer than twelve hours which is the recommended number not to exceed (Thorpy, 2010).  The two negative consequences of the DuPont schedule is the four-day consecutive night shift which can also cause fatigue, plus it has been reported that some employees have a difficult time re-adjusting to work after seven days off (Arnold & Itkin LLP, 2015).

Please click on the following link for detailed information on the DuPont work rotation schedule.http://www.bmscentral.com/learn-employee-scheduling/dupont-shift-schedule/

References

Arnold & Itkin LLP. (2015, June 16). 12-hour shift schedules: Pros & cons of the most common schedules [Web log post]. Retrieved from https://www.industrialinjuryattorney.com/Industrial-Accident-Blog/2015/June/12-Hour-Shift-Schedules-Pros-Cons-of-the-Most-Co.aspx

Business Management Systems. (n.d.). DuPont shift schedule | 24/7 Shift Coverage. Retrieved from http://www.bmscentral.com/learn-employee-scheduling/dupont-shift-schedule/

Culepper, L. C. (2010). The social and economic burden of shit-work disorder. Supplement to The Journal of Family Practice, 59(1), S3-S11. Retrieved from http://media.mycme.com/documents/29/culpepper_2010_swd_suppl_7021.pdf

Drake, C. L. (2010). The characterization and pathology of circadian rhythm sleep disorders. Supplement to The Journal of Family Practice, 59(1), S12-S17. Retrieved from http://media.mycme.com/documents/29/culpepper_2010_swd_suppl_7021.pdf

Embry-Riddle Aeronautical University. (n.d.). 5.4 Research: Shift work schedule. Retrieved from https://erau.instructure.com/courses/73496/assignments/1214117?module_item_id=3890651

Thompson, W. T., Lopez, N., DaLuz, C., & Caldwell, J. L. (2006). Effects of sift work and sustained operations: Operator performance in remotely piloted aircraft (OP-REPAIR) (HSW-PE-BR-TR-2006-0001). United States Air Force 311th Human Systems Wing. Retrieved from website: http://www.dtic.mil/dtic/tr/fulltext/u2/a443145.pdf

Thorpy, M. J. (2010). Managing the patient with shift-work disorder. Supplement to The Journal of Family Practice, 59(1), S24-S31. Retrieved from http://media.mycme.com/documents/29/culpepper_2010_swd_suppl_7021.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 crewmembers (NPS-OR-08-001). Monterey, CA: Naval Postgraduate School. Retrieved from http://www.dtic.mil/dtic/tr/fulltext/u2/a477976.pdf

           

Research Assignment: UAS Beyond Line of Sight Operations

Gabriel P. Riccio

ASCI 638 Human Factors in Unmanned Systems

Embry-Riddle Aeronautical University-Worldwide

3 February 2018

Research Assignment: UAS Integration in the NAS

Introduction

            The next big step in the advancement of Unmanned Aerial Systems (UAS) is the integration of commercial platforms into the National Airspace System (NAS) that operate beyond line of sight (BLOS).  The Federal Aviation Administration (FAA) is currently developing regulatory strategies and developing draft regulations to facilitate commercial (BLOS) operations (Plaza, 2017).  Part of these strategies include the development of UAS detection and avoidance systems that allow the air vehicles to detect both static and moving objects within their flight environment (Plaza, 2017).  Most recently the Trump administration announced that it is instituting a program that will begin the integration of BLOS operations for commercial UAS (Margaritoff, 2017).  The purpose of this program is to develop legislation that allows governmental and commercial UAS entities to fly BLOS for such purposes as infrastructure inspections, emergency management operations, and the commercial delivery of packages (Margaritoff, 2017).  The current reality is that there are very limited and heavily restricted civilian BLOS UAS flight operations and most of that is for testing purposes.  The one organization that has been flying unmanned platforms BLOS for several years is the United States Department of Defense (DOD), and perhaps one of the most well-known and significant is the MQ-9 Reaper.

MQ-9 Reaper

            The MQ-9 Reaper is a military UAS designed to find enemy targets, track those targets, then destroy them (Beno, Adamcik Jr., &, Slovakia, 2014).  The Reaper is outfitted with a state of the art management system; it is a fully autonomous platform from take-off to landing without any human pilot control inputs (Beno, Adamcik Jr., &, Slovakia, 2014).  However, it is important to note that the systems ground control station (GCS) pilot can take control of the air vehicle at any time (Beno, Adamcik Jr., &, Slovakia, 2014).  The platform can be controlled via line of sight (LOS) or BLOS based on mission parameters.  LOS command and control is achieved by direct management using portable control (laptops and antennas) or the systems mobile GCS (Beno, Adamcik Jr., &, Slovakia, 2014).  For all BLOS missions, the mobile GCS must be used, see Figure 1 below (Beno & Adamcik Jr., &, Slovakia, 2014).

Figure 1. MQ-9 Reaper GCS. Reprinted from “Unmanned Combat Air Vehicle: MQ-9 Reaper” by V. Beno, F. Adamcik Jr., & K.  Slovakia, 2014, p. 6. Paper presented at International Conference of Scientific Paper.

The communication link for LOS operations is in the C-band spectrum while BLOS flight is achieved with Ku-Band in the ultra-high frequency range (Beno, Adamcik Jr., &, Slovakia, 2014).  The advantages of C-band frequencies are lower costs, wider communications coverage, and minimal effects from rain (Rambharos, 2014).  The disadvantages of C-band communications are the requirements of a large antenna with a higher power output, additionally, C-band frequencies can suffer from interference issues (Rambharos, 2014). Ku-Band frequencies require smaller antennas, do not need as much power as C-Band, and are resistant to interference; the two biggest disadvantages are the negative effects of rain and the beam footprint is very narrow (Rambharos, 2014).

Human Factors in BLOS Operations

            While operating the UAS within LOS, the pilot has “eyes on”, not only of the air vehicle but situational awareness of the operating environment.  When control is BLOS, the GCS pilot and sensor operator must completely rely on the GCS monitors for platform information. The pilot and sensor operator’s world is confined to sensory information transmitted to the GCS via the communications data link.  There is total reliance on automation and platform autonomy; therefore, it is imperative the two-person GCS personnel are able to understand and control their remote environment.

Future Commercial BLOS Operations

            As stated in the “Introduction”, the FAA is aggressively working to integrate commercial UAS into the NAS.  This integration will include UAS that operate BLOS.  There are many challenges yet to be solved in both airspace integration and technologies.  Military BLOS UAS operations take place in special airspace operating environments.  Commercial applications will have to overcome the challenges of effective “see and avoid” operations, along with effectively communicating with other aircraft and air traffic control.

References

Beno, V., Adamcik Jr., F. & Slovakia, K.  (2014, May). Unmanned combat air vehicle: MQ-9 Reaper. Paper presented at International Conference of Scientific Paper. Retrieved from http://www.afahc.ro/ro/afases/2014/forte/BENO.pdf

Margaritoff, M. (2017, October 24). Trump administration expands drone use to beyond visual line of sight. Retrieved from http://www.thedrive.com/aerial/15458/trump-administration-expands-drone-use-to-beyond-visual-line-of-sight

Plaza, J. (2017, January 30). Beyond visual line of sight O\operations: The next target for FAA regulation. Retrieved from https://www.expouav.com/news/latest/beyond-visual-line-sight-operations-next-target-faa-regulation/

Rambharos, A. (2014, October). Satellite communications [Power Point]. Retrieved from http://www.itso.int/images/stories/Capacity-Building/South-Africa-2015/Day2/A-JHB-D1-C-satellite-comms.pdf

Research Assignment: UAS Integration in the NAS

Gabriel P. Riccio

ASCI 638 Human Factors in Unmanned Systems

Embry-Riddle Aeronautical University-Worldwide

25 January 2018 

 Research Assignment: UAS Integration in the NAS

Introduction

            Public law 108-176 titled “Vision 100 - Century of Aviation Reauthorization Act” published in December 2003 laid the foundation for the Federal Aviation Administration (FAA) Next Generation Air Transportation System; referred to as NextGen (Embry-Riddle Aeronautical University [ERAU], 2017).  In December 2004 the Department of Transportation (DOT) presented its NextGen integration system creation plan that cited the programs “goals, objectives, and requirements” (ERAU, 2017).  The purpose of NextGen is to combine newer and innovative technologies that work collectively to make flying not only more efficient, but safer (Federal Aviation Administration [FAA], 2017a).

NextGen Goals

According to the FAA website “What is NextGen”, the goals are to “increase the safety, efficiency, capacity, predictability, and resiliency of American aviation” (FAA, 2017b).  These goals will be accomplished through improvements to commercial airline passenger travel (better experience), operational fuel savings, direct flying routes which not only reduce travel time but lower environmental emissions, reduced aircraft congestion, better communication between controllers and airspace users, standardized weather information access, and improved on-board aircraft technologies (Houston, 2017).  Some of the technologies that will help the FAA achieve the goals of NextGen include the following:

·         Automatic Dependent Surveillance–Broadcast (ADS-B) – When equipped, aircraft can broadcast their location, speed, altitude, and other pertinent information to air traffic control as well as other aircraft.

·         System-Wide Information Management (SWIM) – Improved FAA system to efficiently manage, standardize, secure and control data.

·         Data Communications (Data Comm) – Allows pilots and controllers to communicate via digital text; such as clearances and other instructions.

·         Common Support Service–Weather (CSS-Wx) – One source standardized weather information.

·         Other technologies include the sharing of aviation safety reports, reducing aircraft separation standards due to improved systems, ATC shift from clearance based to trajectory-based operations, and improved flight deck enchantments (Houston, 2017).

NextGen and UAS

            The FAA has targeted the integration of UAS into NextGen in by the year 2025 (Shah, 2013).  In an effort to address the challenges and issues with UAS integration, the U. S. Department of Transportation (DOT) Joint Planning Development Office (JPDO) has created the UAS Research, Development, and Demonstration (RD&D) Roadmap as well as the UAS Comprehensive Plan (Shah, 2013).  The JPDO has identified communications, airspace operations, unmanned aircraft, and human systems integration as the challenge areas (Shah, 2013).  Within each of these identified integration challenge areas, there are a multitude of issues and sub-issues that must be overcome to realize effective UAS integration into the NAS; this is a complex problem that involves several stakeholders along with further research and testing (JPDO, 2012).  There are currently many significant questions yet to be answered such as what are the baseline performance requirements, what are the metrics to determine a baseline performance, what regulatory gaps currently exist, and what technology gaps currently exist (JPDO, 2012).

Human Factors

            UAS integration into the NextGen NAS cannot be accomplished without serious consideration to human factors.  The JPDO identified in its 2012 report several human systems integration issues; these include display of traffic airspace information, effective interaction between humans and automation, a pilot-centric ground control station, clear definition of human roles and responsibilities during UAS operations, predictability of operations, contingency operations, training and qualifications, and support for future operations (JPDO, 2012).  Experts in the field of human factors have also identified some potentially problematic areas of concern relating to NextGen integration.  These concerns center around the unintentional or unforeseen consequences of integration, the underestimation of human-in-the-loop simulations, and non-acceptance on behalf of the users (Beard, Seely, Holbrook, Galeon, 2013).  Some solutions that address the shortcomings of human factors include a FAA budget that supports human performance metrics, access to data that measures human performance so as to make better decisions, and effective collaborations between the FAA and human factor experts (Beard et al., 2013).

  References

Beard, B. L., Seely, R., Holbrook, J., & Galeon, M. (2013). The insertion of human factors concerns into nextgen programmatic decisions. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 57(1), 91-95. 10.1177/1541931213571022

Embry-Riddle Aeronautical University. (2017). What is NextGen. Retrieved from https://nextgen.erau.edu/what-is-nextgen/

Federal Aviation Administration. (2017a, December 6). Modernization of U.S. Airspace. Retrieved from https://www.faa.gov/nextgen/

Federal Aviation Administration. (2017b, November 21). What is NextGen? Retrieved from https://www.faa.gov/nextgen/what_is_nextgen/

Houston, S. (2017, June 25). NextGen in a nutshell: The next generation air traffic system. Retrieved from https://www.thebalance.com/nextgen-in-a-nutshell-282561

Joint Planning and Development Office. (2012). NextGen UAS research, development and demonstration roadmap. Version 1.0 (ADA561097). Retrieved from http://www.dtic.mil/dtic/tr/fulltext/u2/a561097.pdf

Shah, Y. (2013, April). Joint planning and development office (JPDO) Unmanned aircraft systems (UAS). Paper presented at Integrated Communications, Navigation and Surveillance Conference, Herndon, VA. http://dx.doi.org/10.1109/ICNSurv.2013.6548689

Research Assignment: UAS GCS Human Factors Issue

Gabriel P. Riccio

ASCI 638 Human Factors in Unmanned Systems

Embry-Riddle Aeronautical University-Worldwide

17 January 2018

Introduction

            The primary purpose of the unmanned aerial system (UAS) ground control station (GCS) is to provide the interface between the human in-the-loop and the air vehicle; its complexity is dependent on the overall UAS command, control, and communication requirements (Austin, 2010).  The GCS could be a simple hand-held device from which the operator does mission planning, then executes the mission or part of a sophisticated network-centric system architecture (Austin, 2010).  No matter how the GCS is designed and engineered it must be functional, not only from the perspective of the air vehicle but from the perspective of the operator. The GCS design must consider both human factors and pilot ergonomics.  Currently, most UAS GCSs are responsible for the operation of only one air vehicle at a time.  As UAS gain greater autonomy and develop greater interoperability capabilities it is likely that the GCS operator will be able to effectively control a multitude of unmanned air vehicles at any given time (Bhalla, 2015). 

Multi-UAS GCS

            The paper titled “A Ground Control Station for a Multi-UAV Surveillance System: Design and Validation in Field Experiments” by D. Perez, I. Maza, F. Caballero, D. Scarlatti, E. Casado, A. & Ollero (2013) examines a GCS that was designed for an operator to simultaneously manage multiple small UAS (sUAS) at any given time for the purpose of surveillance missions.  The primary design goal was to reduce the workload of the pilot who directly supervises multiple unmanned air vehicles that coordinate and interact with one another to a manageable level by simplifying GCS command and control functionality (Perez, Maza, Caballero, Scarlatti, Casado, & Ollero, 2013).  During the GCS design process, several necessary attributes were identified:

·         The GCS is capable of autonomously knowing when an air vehicle enters or departs the environment.

·         The GCS has built-in visual alerts to inform the pilot of any system advisories such as a low battery or cautions associated with malfunctioning equipment.

·         The GCS gives the operator the capability to display air vehicle status; the operator gets to choose what vehicles and the number of vehicles; to prevent information overload but maintain situational awareness.

·         The air vehicles themselves in this scenario possess some decisional autonomy, which do not require constant direct supervision (Perez et al., 2013).

The hardware that makes up the GCS is a mobile laptop computer that communicates to the air vehicles via a wireless local area network (WLAN) and router (Perez et al., 2013).  During testing of the GCS, the researchers used two additional laptops for improved platform supervision; two platforms were used during testing but it must be noted that a single computer with its associated software is capable of managing all aircraft (Perez et al., 2013).  The computer screen layout of the GCS has four main areas: an air vehicles selector, selected air vehicle information, interactive map, and application widgets (Perez et al., 2013).

            The researchers’ concluded that the GCS system architecture proved to be capable of command, control, and effective communication with multiple sUAS conducting surveillance missions. The GCS also worked well with the autonomous features integrated into the air vehicles (Perez et al., 2013).  In the future, the researchers’ hope to locate the GCS to a remote location and control all activities via the internet (Perez et al., 2013).

Negative Human Factors

            Two negative human factors issues can be associated with this GCS.  The first is the potential for information overload which could potentially confuse the operator or cause them to make a poor decision.  When everything is working, operator workload is low, this is mostly due to the autonomous behaviors of the individual platforms.  If the operator has to manage more than one problem at a time, they could easily become distracted and lose mission situational awareness.  The second issue is information overload.  A single operator could easily become task saturated trying to monitor several sUAS, especially during a surveillance mission and may have difficulty prioritizing the work.  During field testing experiments, only two sUAS were utilized but there is most likely is a point in which one single GCS operator can manage so many sUAS at any given time while still carrying out the mission.  As in manned aircraft, system failures and emergencies can easily overwhelm the pilot or pilots.  It is important to ensure each mission has the appropriate number of fully trained pilots and support personnel.

References

Austin, R. (2010). Unmanned aircraft systems: uavs design, development and deployment. Chichester: Wiley. Retrieved from https://ebookcentral-proquest-com.ezproxy.libproxy.db.erau.edu/lib/erau/detail.action?docID=514439

Bhalla, P. (2015). Emerging trends in unmanned aerial systems. Scholar Warrior, Autumn 2015, 86-94. Retrieved from www.claws.in/images/journals_doc/1119543205_Emergingtrendsinunmannedaerialsystems.pdf

Perez, D., Maza, I., Caballero, F., Scarlatti, D., Casado, E., & Ollero, A. (2013). A ground control station for a multi-UAV surveillance system: Design and validation in field experiments. Journal of Intelligent & Robotic Systems, 69(1), 119-130. http://dx.doi.org/10.1007/s10846-012-9759-5

9.4 The Future of the UAS

One does not have to search long to find articles on the future integration of unmanned passenger aircraft in the National Airspace System (NAS). The article titled “Pilotless Planes Could be Possible by 2025” by R. Ahluwalia (2017) discusses technologies currently being developed that could take pilots out of the cockpit of passenger airliners. The article cites the two major advantages of removing pilots are a significant savings in the “cost of employing pilots” and increased flight safety; since there will be no pilot error (Ahluwalia, 2017). The article bases its conclusion on research conducted by UBS; the investment bank. 

The UBS 53 page research paper states that by the year 2025 it is technology feasible that commercial air traffic could be unmanned (Castle et al., 2017). This idea works well for cargo carrying aircraft but maybe not so much for passenger airliners. According to a survey conducted by UBS, 54% of 8,000 survey respondents reported they will not fly on an unmanned aircraft (Ahluwalia, 2017). To overcome the fears of flying on board an aircraft without a pilot the approach may need to be incremental. The first step would be to reduce the requirement from two pilots to one pilot operations (Castle et al., 2017). 

Boeing is currently studying the potential for replacing pilots with artificial intelligence (Gates, 2017). Boeing believes they can produce unmanned autonomous aircraft with the same level of safety currently realized by manned airliners but there are still many challenges that need to be overcome (Gates, 2017). When an aircraft experiences an unexpected emergency, pilots often have to immediately analyze the situation and make a decision of action; it is impossible to pre-program every scenario. Therefore, it is essential that the onboard artificial intelligence is capable to independently react as a pilot would (Gates, 2017). 

Current Federal Aviation Regulations (FAR) do not support the use or integration of unmanned commercial airlines in the National Airspace System (NAS). So even if unmanned airliner technologies prove to be a realistic scenario by 2025, the FAA must approve their operations which includes all phases of flight and ground operations. According to the USB research report: 

“ the full FAA registration of a commercial plane would need to cover a number of areas around the current design certification process, such as aircraft certification software, automated conformity inspection, original design approval, technical standards, and safety and product certification, which, we believe, would need to be expanded on to allow for pilotless planes” (Castle et al., 2017, p.26). 

Additional points of concern revolve around security, health and safety, and resistance from the pilot’s themselves and their union (Castel, et al., 2017). What needs to be understood is that this is coming. It will be an incremental approach and start with cargo aircraft, and will most likely begin with reducing the cockpit to one pilot with a robotic co-pilot onboard or another pilot monitoring the flight from a Ground Control Station (GCS) who has the ability to remotely control the platform if needed. Over time FAA regulations will have to evolve to support these type of operations. 

References

Ahluwalia, R. (2017, August 10). Pilotless planes could be here within 10 years. Retrieved from http://www.independent.co.uk/travel/news-and-advice/pilotless-plane-remote-controlled-flight-drone-aircraft-2025-aviation-technology-a7884911.html 

Castle, J., Fornaro, C., Genovesi, D., Lin, E., Strauss, D., Wadewitz, T., & Edridge, D. (2017). Flying solo - how far are we down the path towards pilotless planes. Retrieved from http://nzz-files-prod.s3-website-eu-west-1.amazonaws.com/2017/8/7/93872795-5ab9-4f94-bb3a-f6ed38c6b886.pdf 

Gates, D. (2017, June 8). Boeing studies planes without pilots, plans experiments next year. The Seattle Times. Retrieved from https://www.seattletimes.com/business/boeing-aerospace/boeing-studies-planes-without-pilots-plans-experiments-next-year/