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Incorporating UAS into Airport InfrastructureâPlanning Guidebook Â 109 9 Appendix: UAS Forecast Process Step 1: Gather Current UAS Forecast Data Several industry and governmental forecasts related to military, non-model, civil and commercial UAS were published by the TEAL Group, US 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 US DOT and FAA Aerospace UAS forecasts provided the most consistent and realistic estimates of likely UAS demand in the United States during the next 10+ years. Table 14 and Table 15 highlight the US DOT and FAA UAS forecasts. Table 14 : US DOT forecasts for UAS (commercial, public, and DOD) (USAF, 2013) and (DOD, 2005) Year Total UAS Activity Commercial Only UAS All Other Public Agencies including US DOD US DOD Only â 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 15 : FAA forecasts for UAS (FAA, 2018) Total Non-Model Fleet Year Base High 2017 110,604 110,604 Forecast 2018 158,900 168,339 2019 229,400 268,937
Incorporating UAS into Airport InfrastructureâPlanning Guidebook Â 110 Total Non-Model Fleet 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% 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, GA airport), infrastructure (on-site ATCT, available apron, hangar and land, and type and condition of runways), and other socio-economic 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 activity forecasts (e.g. master plan and state aviation system plan). This data can be used to establish 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 âbest guessâ 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. Step 4: Create Range Forecasts, Apply Forecast Methods, and Evaluate Results
Incorporating UAS into Airport InfrastructureâPlanning Guidebook Â 111 FAA Personnel (Conference Call with FAA Forecasting Branch, 2018) within 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 international 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 âaircraftâ and operations are already included in the airportâs 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 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 substantially 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 US 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 FAAâs 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, GA airports. According to FAA Order 5090.3C, Field Formulation of National Plan of Integrated Airport Systems, which is currently being updated, forecasts traditionally should not vary significantly (more than 10 percent) from the FAAâs forecast to be approved and incorporated into the TAF and National Plan of Integrated Airport Systems (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. runway 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. 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
Incorporating UAS into Airport InfrastructureâPlanning Guidebook Â 112 UAS (i.e., Global Hawk) as well as developing pilot on-board options UAS, and manufactures 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 pounds are based upon existing manned aircraft airframes. Therefore, using weight and operating requirements, UAS were categorized as follows: Table 16 : UAS fleet mix category descriptions 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 8â > 20â /8â to 40â 50 to 75 <10,000 5 to 25 Ultralight UAS Airframe 55 to 255 <30 9â > 40â 75 to 150 <15,000 50 to 100 Light Sport UAS Airframe 255 to 1,320 <45 15â >45â 75 to 150 <18,000 100 to 200 Small UAS Airframe/Rotorcraft 1,320 to 12,500 <60 <79â/<40â 100 to 200 <25,000 100 to 200 Medium UAS Airframe 12,500 to 41,000 60 > 95 79â>139â/40â>55â Est. 100 to 200 <100,000 TBD Large UAS Airframe >41,000 >95 >139â*/> 55â 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: US DOT UAS Forecast, Table 8, Volpe UAS Activity Forecasts, FAA Aircraft Data, ultralight manufacturer aircraft data, UAS rotorcraft blade sellers, and UAS manufacturers, 2018, US Department of Defense Report, Drone Report 2018, Military Drones Specifications, and
Incorporating UAS into Airport InfrastructureâPlanning Guidebook Â 113 Type of UAS Weight (lbs.) Estimated Size (ft.) Approximate Wingspan/Rotor Blades (Ft) Mission Speed (MPH) Mission Altitude (ft above surface) Mission Radius (Miles) Commercial Industry UAS criteria, Department of Geography at Penn State University, and Astrid Aviation and Aerospace 2018 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 operations 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 pounds) will represent the majority of 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 17. Table 17 : Estimated percentage of total forecast UAS operations likely to occur at an airport 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 US UAS Operations likely to occur at US 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 US 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
Incorporating UAS into Airport InfrastructureâPlanning Guidebook Â 114 Type of UAS 2017 2018 2023 2028 2033 2038 Tech Forecasts of UAS Demand, Boeing bets big on flying taxis and pilotless planes, and Astrid Aviation and Aerospace 2018. Using the data above, 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 airports 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 18 demonstrates the likely breakdown of UAS by type during the planning period. Table 18 : Estimated airport UAS fleet mix 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% 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 donât support substantial military operations. Applying this data to total forecast UAS operations, results in an estimate of likely operations by type which may then be used along with manned forecast fleet mix data to determine 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.
Incorporating UAS into Airport InfrastructureâPlanning Guidebook Â 115 Anticipated growth will also be impacted by regulatory requirements and public acceptance of new technology.