Airports and Unmanned Aircraft Systems, Volume 2: Incorporating UAS into Airport Infrastructure— Planning Guidebook (2020)

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C-1 Step 1: Gather Current UAS Forecast Data Several industry and governmental forecasts related to military, non-model, civil and commercial UAS were published by Teal Group, U.S. DOT/VOLPE, FAA, Business Insider, as well as other industry and academic organizations. UAS growth ranged from 3 to 51 percent during a 20+ year average forecast period. Given differences in how data was reported and variations in baseline information, the U.S. DOT and FAA Aerospace UAS forecasts pro- vided the most consistent and realistic estimates of likely UAS demand in the United States during the next 10+ years. Tables C-1 and C-2. highlight the U.S. DOT and FAA UAS forecasts. This data is used to extract current trends regarding UAS operations, which then may be modified when applied to each individual airport considering various operational (e.g. commercial hub, non-hub, general aviation airport), infrastructure (on-site ATCT, avail- able apron, hangar and land, and type and condition of runways), and other socioeconomic factors (e.g. support of community and stakeholders). Step 2: Gather Airport Terminal Area Forecast or Approved Master Plan Forecasts Obtain the most current FAA TAF for the airport and most recent approved aviation activ- ity forecasts (e.g. master plan and state aviation system plan). This data can be used to estab- lish likely UAS based aircraft, the type of UAS operations that may occur at the airport on a regular basis (e.g. military, commercial, and general aviation) as well as the likely breakdown between itinerant and local operations given UAS industry data and trends. Step 3: Determine Historical UAS Operations by Type Historical UAS operational data may not be available. No historical UAS operational data was available although the airports had supported some UAS activity. Therefore, if possible, UAS activity should be collected and recorded by the airport. If no UAS activity currently occurs at the airport, using national UAS industry demand and the type of aviation activities currently and likely to occur, airport planners, as they did in the PDT Master Plan, must make a “best guess” estimate of the number, type and timing of when UAS operations may occur at the airport. This information will provide the baseline for future operational and infrastructure assessments. It is important to note that forecasts merely represent likely scenarios of future demand, so estimated baseline data in the forecasts can be shifted forward or back to represent actual demand. A P P E N D I X C UAS Forecast Process

C-2 Airports and Unmanned Aircraft Systems Year Total UAS Activity Commercial Only UAS All Other Public Agencies including U.S. DOD US DOD Only – Unmanned and Pilot Optional 2015 11,000 1,000 10,000 9,005 2021 20,125 5,125 15,000 10,005 2026 50,000 20,000 30,000 12,211 2031 160,000 100,000 60,000 14,813 2035 250,000 175,000 75,000 19,000 AAGR 2015- 2026 15% 31% 7% 3% AAGR 2015- 2035 17% 29% 11% 4% Table C-1. U.S. DOT forecasts for UAS (commercial, public, and DOD) (USAF, 2013; DOD, 2005). Total Non-Model Fleet Year Base High 2017 110,604 110,604 Forecast 2018 158,900 168,339 2019 229,400 268,937 2020 312,100 410,862 2021 407,400 604,550 2022 451,800 717,895 CAGR 2017-2022 33% 45% CAGR 2021-2022 11% 19% 2023 501,039 852,491 2028 840,422 2,012,951 2033 1,409,689 4,753,097 2038 2,364,555 11,223,290 CAGR 2023-2038 11% 19% Table C-2. FAA forecasts for UAS (FAA, 2018).

UAS Forecast Process C-3 Step 4: Create Range Forecasts, Apply Forecast Methods, and Evaluate Results FAA personnel (Conference Call with FAA Forecasting Branch, 2018) within the Office of Aviation Policy and Plans, Statistics, and Forecast Branch (APO-110) anticipate that UAS activity will merely replace general aviation, military and even some commercial operations as outlined in the TAF rather than provide additional operations above those already anticipated. However, UAS users, published information from DOT and DOD, and other U.S. and inter- national organizations and agencies anticipate that UAS will not only replace some manned aircraft but will also add aircraft into the worldwide fleet. As a result, a range forecast consisting of three models (low, mid and high) can evaluate potential demand given various scenarios. Low Forecasts: The low forecast assumes that UAS based “aircraft” and operations are already included in the airport’s TAF forecast. This forecast assumes that UAS operations will replace manned aircraft operations on a one-to-one basis. Mid-Forecasts: The mid-forecast assumes that UAS activity will not only add to forecast demand, but in the long-run also replace some manned activity. The likely percentage of aircraft and operations replaced may be determined considering current and anticipated activity at the airport, operating missions, as well as type and size of likely UAS activity. High Forecasts: The high forecasts anticipate that a limited number of manned aircraft, if any, will be replaced by UAS given the types of activity currently occurring and anticipated to occur at the airport. Thus, most of the forecast demand is added to forecast activity in the TAF. The range forecasts may be developed using either a recently approved airport aviation activity forecast or the most recent FAA TAF. If the TAF forecast base year differs substan- tially from data provided by the airport in its Airport Master Record, the TAF forecast base year may be updated to reflect actual airport activity. Applying growth rates provided from the U.S. DOT 2015–2035, FAA Aerospace Forecasts, 2018–2038, UAS and manned aircraft demand forecasts can be created. Step 5: Compare to TAF Since the FAA does not currently review or approve UAS-specific forecasts, this step is optional. However, given the unique nature of UAS forecasting and FAA’s interest in evaluating the impacts of UAS on the aviation system, a comparison between the forecasts could highlight some needed changes in the governmental forecasting methodologies especially at small general aviation airports. According to FAA Order 5090.3C, Field Formulation of National Plan of Inte- grated Airport Systems, which is currently being updated, forecasts traditionally should not vary significantly (more than 10 percent) from the FAA’s forecast to be approved and incorporated into the TAF and NPIAS. However, even if proposed operational forecasts exceed 10 percent, due to the unique nature of UAS and aviation industry trends, the FAA may ultimately incorporate this information into state, TAF and NPIAS forecasts for future years. Ultimately, this incorporation would clear another hurdle to possible funding for UAS infrastructure improvements. Step 6: Determine Fleet Mix Forecast The purpose of a fleet mix forecast is to determine likely critical aircraft demand and to provide a baseline for identifying existing and future airport infrastructure needs (e.g. run- way length, pavement strength, and hangar size). Fleet mix source data can be obtained from official airline guides and T-100 data for commercial aircraft activity in addition to airport users and stakeholders.

C-4 Airports and Unmanned Aircraft Systems As noted earlier, due to the size of current UAS and operating needs, the majority of UAS do not regularly, if at all, use traditional airport infrastructure. However, the military is actively using larger UAS (i.e., Global Hawk) as well as developing pilot onboard options for UAS, and manufacturers are currently designing and testing larger UAS for various commercial uses (e.g. passenger transport, cargo transport, search and rescue, and firefighting). Thus, it is expected, given current development and testing of larger UAS, that as UAS become larger and more sophisticated, their use of airport facilities will likely increase. Based upon information provided by UAS manufacturers such as Boeing, Airbus, Northrop Grumman, and Lockheed, platforms for UAS greater than 100 lbs are based upon existing manned aircraft airframes. Therefore, using weight and operating requirements, UAS were categorized as shown in Table C-3. Using UAS size information and existing fleet mix data obtained from DOD and other aviation models (e.g. Teal Forecasts, Business Insider, and IBISworld) as well as historical data from airports currently supporting UAS activity, a breakdown of likely UAS opera- tions by aircraft type was created. Historical and forecast data provided by governments and industry show that airport use by small UAS (4.5 to 55 lbs) will represent the majority of Type of UAS Weight (lbs.) Estimated Size (ft.) Approximate Wingspan/Rotor Blades (Ft) Mission Speed (MPH) Mission Altitude (ft above surface) Mission Radius (Miles) Nano <1 0.98-1.64 <1.15 Varies <30 feet < 1 Micro (based on Black Hornet 3) <4.5 < 4 < 8 <13 <400 < 1.5 Small UAS 4.5 to 55 4<10 8’ > 20’ /8” to 40” 50 to 75 <10,000 5 to 25 Ultralight UAS Airframe 55 to 255 <30 9’ > 40’ 75 to 150 <15,000 50 to 100 Light Sport UAS Airframe 255 to 1,320 <45 15’ >45’ 75 to 150 <18,000 100 to 200 Small UAS Airframe/Rotorcraft 1,320 to 12,500 <60 <79’/<40’ 100 to 200 <25,000 100 to 200 Medium UAS Airframe 12,500 to 41,000 60 > 95 79’>139’/40’>55’ Est. 100 to 200 <100,000 TBD Large UAS Airframe >41,000 >95 >139’*/> 55’ Est. >140 >100,000 TBD Notes: 139-foot wingspan information was obtained from discussion with Mr. Michael Hainsey AAE, Executive Director, Golden Triangle Regional Airport. Current tenant Northrop Grumman is currently building and testing these UAS/Drone wings at his facility. Sources: U.S. DOT UAS Forecast, Table 8, Volpe UAS Activity Forecasts, FAA Aircraft Data, ultralight manufacturer aircraft data, UAS rotorcraft blade sellers, and UAS manufacturers, 2018, U.S. DOD Report, Drone Report 2018, Military Drones Specifications, and Commercial Industry UAS criteria, Department of Geography at Penn State University, and Astrid Aviation and Aerospace 2018. Table C-3. UAS fleet mix category descriptions.

UAS Forecast Process C-5 UAS operations in the near term. However, as the size of UAS aircraft increase and resemble traditional aircraft, use of airports is also expected to increase. The likely breakdown of UAS activity at airports is provided in Table C-4. Using the data in Table C-4, each type of UAS may be divided by the percent of the total estimated UAS fleet anticipated to regularly use an airport. For example, small UAS using air- ports in 2017 is estimated at 6 percent. Dividing that 6 percent by 6.38 percent, the total percentage of the UAS fleet likely to operate at an airport, results in an estimate that 94 percent of those UAS operations will be associated with small UAS activity. Likely small UAS operating at an Airport = 6%/6.38% = 94% of total UAS Airport Operations would be Small UAS Table C-5 demonstrates the likely breakdown of UAS by type during the planning period. Note, this is an estimate given current market conditions, UAS industry trends and current UAS data. This analysis also considered that airports support some level of military operations. Therefore, the percentage of large UAS estimated may be higher than other similarly sized airports that don’t support substantial military operations. Type of UAS 2017 2018 2023 2028 2033 2038 Nano 0% 0% 0% 0% 0% 0% Micro 0% 0% 0% 0% 0% 0% Small UAS* 6% 6% 7% 8.00% 8.30% 8.60% Ultralight UAS Airframe** 0.38% 0.54% 4.00% 5.00% 5.00% 5.00% Light Sport UAS Airframe** 0.00% 0.03% 4.00% 6.00% 7.00% 8.00% Small UAS Airframe/Rotorcraft** 0.00% 0.00% 3.00% 6.50% 6.50% 6.50% Medium UAS Airframe** 0.00% 0.00% 2.00% 6.00% 8.00% 8.00% Large UAS Airframe** 0.00% 0.00% 0.00% 4.00% 4.00% 6.00% Estimated Percent of Total UAS Operations likely to occur at U.S. Airports 6.38% 6.57% 20.00% 35.50% 38.80% 42.10% Notes: * Small UAS is expected to be used based upon historical and current data by airport operators as well as for UAS training. ** These are in development and are being tested. Some include new designs and others involve conversion of approved aircraft airframes. Due to rounding, numbers may not add up to total. Note of sources: These data were gathered from discussions with existing and potential users, FAA test site management, Searchlight Airport Management, GSP Management, FAA Aerospace Forecasts and U.S. DOT UAS Forecast 2015-35, The Teal Group Worldwide UAS Forecast, 2017-2037, Unmanned Aircraft Systems, 2015; U.S. DOT Unmanned Aircraft System (UAS) Service Demand, 2015-2035; Business Insider Tech Forecasts of UAS Demand, Boeing bets big on flying taxis and pilotless planes, and Astrid Aviation and Aerospace 2018. Table C-4. Estimated percentage of total forecast UAS operations likely to occur at an airport.

C-6 Airports and Unmanned Aircraft Systems Applying this data to total forecast UAS operations, results in an estimate of likely opera- tions by type which may then be used along with manned forecast fleet mix data to deter- mine the critical aircraft or group of critical aircraft requirements. It is important to note that activity forecasts become less reliable the further out they project due to expected changes in technology, consumer demand and overall aviation activity volatility. Anticipated growth will also be impacted by regulatory requirements and public acceptance of new technology. Type of UAS 2017 2018 2023 2028 2033 2038 Small UAS 94% 91% 35% 23% 21% 20% Ultralight UAS Airframe* 6% 8% 20% 14% 13% 12% Light Sport UAS Airframe* 0% 0% 20% 17% 18% 19% Small UAS Airframe/Rotorcraft* 0% 0% 15% 18% 17% 15% Medium UAS Airframe* 0% 0% 10% 17% 21% 19% Large UAS Airframe* 0% 0% 0% 11% 10% 14% TOTAL 100% 100% 100% 100% 100% 100% Table C-5. Estimated airport UAS fleet mix.