National Academies Press: OpenBook

Airport Curbside and Terminal Area Roadway Operations (2010)

Chapter: Chapter 3 - Estimating Airport Roadway Traffic Volumes

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Suggested Citation:"Chapter 3 - Estimating Airport Roadway Traffic Volumes." National Academies of Sciences, Engineering, and Medicine. 2010. Airport Curbside and Terminal Area Roadway Operations. Washington, DC: The National Academies Press. doi: 10.17226/14451.
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Suggested Citation:"Chapter 3 - Estimating Airport Roadway Traffic Volumes." National Academies of Sciences, Engineering, and Medicine. 2010. Airport Curbside and Terminal Area Roadway Operations. Washington, DC: The National Academies Press. doi: 10.17226/14451.
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Suggested Citation:"Chapter 3 - Estimating Airport Roadway Traffic Volumes." National Academies of Sciences, Engineering, and Medicine. 2010. Airport Curbside and Terminal Area Roadway Operations. Washington, DC: The National Academies Press. doi: 10.17226/14451.
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Suggested Citation:"Chapter 3 - Estimating Airport Roadway Traffic Volumes." National Academies of Sciences, Engineering, and Medicine. 2010. Airport Curbside and Terminal Area Roadway Operations. Washington, DC: The National Academies Press. doi: 10.17226/14451.
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Suggested Citation:"Chapter 3 - Estimating Airport Roadway Traffic Volumes." National Academies of Sciences, Engineering, and Medicine. 2010. Airport Curbside and Terminal Area Roadway Operations. Washington, DC: The National Academies Press. doi: 10.17226/14451.
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Suggested Citation:"Chapter 3 - Estimating Airport Roadway Traffic Volumes." National Academies of Sciences, Engineering, and Medicine. 2010. Airport Curbside and Terminal Area Roadway Operations. Washington, DC: The National Academies Press. doi: 10.17226/14451.
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Suggested Citation:"Chapter 3 - Estimating Airport Roadway Traffic Volumes." National Academies of Sciences, Engineering, and Medicine. 2010. Airport Curbside and Terminal Area Roadway Operations. Washington, DC: The National Academies Press. doi: 10.17226/14451.
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Suggested Citation:"Chapter 3 - Estimating Airport Roadway Traffic Volumes." National Academies of Sciences, Engineering, and Medicine. 2010. Airport Curbside and Terminal Area Roadway Operations. Washington, DC: The National Academies Press. doi: 10.17226/14451.
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Suggested Citation:"Chapter 3 - Estimating Airport Roadway Traffic Volumes." National Academies of Sciences, Engineering, and Medicine. 2010. Airport Curbside and Terminal Area Roadway Operations. Washington, DC: The National Academies Press. doi: 10.17226/14451.
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Suggested Citation:"Chapter 3 - Estimating Airport Roadway Traffic Volumes." National Academies of Sciences, Engineering, and Medicine. 2010. Airport Curbside and Terminal Area Roadway Operations. Washington, DC: The National Academies Press. doi: 10.17226/14451.
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Suggested Citation:"Chapter 3 - Estimating Airport Roadway Traffic Volumes." National Academies of Sciences, Engineering, and Medicine. 2010. Airport Curbside and Terminal Area Roadway Operations. Washington, DC: The National Academies Press. doi: 10.17226/14451.
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Suggested Citation:"Chapter 3 - Estimating Airport Roadway Traffic Volumes." National Academies of Sciences, Engineering, and Medicine. 2010. Airport Curbside and Terminal Area Roadway Operations. Washington, DC: The National Academies Press. doi: 10.17226/14451.
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Suggested Citation:"Chapter 3 - Estimating Airport Roadway Traffic Volumes." National Academies of Sciences, Engineering, and Medicine. 2010. Airport Curbside and Terminal Area Roadway Operations. Washington, DC: The National Academies Press. doi: 10.17226/14451.
×
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Suggested Citation:"Chapter 3 - Estimating Airport Roadway Traffic Volumes." National Academies of Sciences, Engineering, and Medicine. 2010. Airport Curbside and Terminal Area Roadway Operations. Washington, DC: The National Academies Press. doi: 10.17226/14451.
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16 This chapter presents methods for estimating existing and future airport roadway requirements. The data required to analyze existing roadway traffic volumes and operations are described, and two alternative methods for estimating future roadway traffic volumes are presented. One method, the tra- ditional four-step approach commonly used by transporta- tion planners, incorporates estimates of the roadway traffic volumes generated by airline passengers, visitors, employees, air cargo handlers, and major airport land uses. This method requires an extensive database for each of these traffic gener- ators. The second method, the growth factor method, yields acceptable, but less precise results, while requiring much less input data. However, this simpler method is less sensitive to changes in future conditions or travel patterns. Establishing Existing Airport Roadway Traffic Volumes Analyses of existing conditions and estimates of future con- ditions should be based on observed vehicular activity. Surveys of traffic volumes, roadway operations, and vehicle character- istics are often conducted to support these analyses. Additional information about traffic surveys can be found in the ITE Man- ual of Traffic Engineering Studies and other references listed in the bibliography provided in Appendix B to this Guide. Roadway Traffic Volume Survey Methods Roadway traffic volumes can be obtained inexpensively and quickly through surveys compared to a planning and forecast- ing analysis. Surveys of roadway traffic can be conducted by (1) the public works or traffic engineering department of a municipality or county using automatic traffic recorders (ATRs), (2) consulting firms that specialize in conducting such surveys, or (3) interns, students, or volunteers recruited to manually record traffic volumes on airport roadways. For example, in 2010 a comprehensive 7-day traffic survey that included installing ATRs at 25 locations typically cost less than $50,000 (or about $1,000 to $2,000 per location) excluding any analyses of the resulting data. If the analysis of roadway operations is to focus on one road- way segment (e.g., a curbside roadway), it may be necessary to record only the traffic volumes on this segment and/or adja- cent roadways rather than to conduct a comprehensive survey of all roadways. Similarly, if peak airport traffic periods are known, it may be possible to record the traffic volumes during a 3-hour peak period coinciding with this peak period rather than conduct day-long, 48-hour, or 7-day surveys. Selecting Survey Dates Ideally, the traffic volume and curbside surveys should be conducted during the peak hours on a typical busy day (ideally during a peak month). Typically, the peak days occur in the months with the largest volumes of airline traffic. At many air- ports, the busiest days are Mondays and Fridays, but at some airports—especially those serving large volumes of non- business passengers—the busiest days may be Sundays. Selecting Survey Hours The peak hours for roadway traffic precede the peak hour for originating airline passenger departures and follow the peak hour for terminating airline passenger arrivals. Peak- hour traffic volumes can be determined by counting the num- bers of vehicles on the roadway by type of vehicle (for curbside surveys), recording the number of vehicles on the roadway during each 15-minute increment, and then either identify- ing the four consecutive 15-minute increments with the largest traffic volumes or the busiest 15-minute increment. It is suggested that surveys of the departures area (passenger drop-off area) roadways be conducted during the 3 hours prior to and including the 60-minute period with the most departing flights, and that surveys of the arrivals area (passen- C H A P T E R 3 Estimating Airport Roadway Traffic Volumes

17 ger pickup area) roadways be conducted during the 3 hours including and after the 60-minute period with the most arriv- ing flights. The 60-minute departures and arrivals flight peaks do not necessarily coincide. Surveys of Traffic Characteristics and Operational Patterns In addition to surveys of traffic volumes, analyses of airport roadway operations frequently require other surveys to deter- mine the following: • Vehicle mix. In an airport environment, vehicle mix (or vehicle classification) refers to the portion of the traffic vol- ume accounted for by individual modes, as defined by both the type of service each mode provides (e.g., taxicab, cour- tesy vehicle, charter bus) and the type of vehicle used (e.g., sedan, passenger van, minibus, full-size bus). These data are required to analyze curbside roadway operations. • Dwell time. This is the amount of time a vehicle spends parked at a curbside lane (or other passenger loading or unloading area). Typically, the dwell time is the length of time between when the driver parks (i.e., the vehicle comes to a complete stop) and when the driver first attempts to rejoin the traffic stream (it does not include any time dur- ing which the driver may be ready to depart, but is pre- vented from doing so by other vehicles). For some analyses, it is also helpful to measure “active” dwell times (i.e., the length of time a vehicle remains at a curbside while actively loading/unloading passengers and their baggage) as opposed to the “total” dwell time, which reflects the time difference between when a vehicle first stops at a curbside until it leaves the curbside. Dwell time data are required to analyze curb- side roadway operations. • Queue length. Queue length is the distance, time, or number of vehicles in a line of vehicles waiting to proceed along a road- way in which (1) the flow rate of the front of the queue deter- mines the average speed within the queue and (2) the rate of vehicles arriving in the queue is greater than the rate of vehi- cles leaving the queue. Queues form when a group of vehicles is delayed because of downstream congestion or bottlenecks. The length of a queue can be measured by observing, at fixed intervals, the length of slow moving or stopped vehicles, and the time of a queue can be measured by observing how long it takes a vehicle to travel from the back to the front of a queue. The number of vehicles in a queue and the duration, or per- sistence, of the queue also can be determined through obser- vations. These data are used to support evaluations of airport roadway operations. • Travel speeds. Average travel speeds can be measured by recording the time it takes random vehicles to travel a known distance, such as between two fixed objects or points. Average travel speeds—particularly along a roadway seg- ment having a length of 1,000 feet or more—can be used to support evaluations of airport roadway operations. Measur- ing instantaneous speeds (also known as spot speeds) is not useful in airport roadway analyses because the speeds of individual vehicles tend to vary significantly on the roadway network. • Other data. In addition to the data listed above, depend- ing on the nature of the traffic operations problem being addressed, data on vehicle mix (i.e., the proportion of pri- vate vehicles, taxicabs, limousines, vans, buses, etc., using the roadways), recirculation volumes (i.e., the proportion of vehicles passing the curbside or other location multiple times, typically determined by recording and matching the license plate numbers of passing vehicles), and curbside occupancies (observations or video recordings of curbside use patterns) are sometimes gathered as part of airport road- way operations analyses. Surveys of airline passengers and visitors are commonly used to gather such data as vehicle mode-choice patterns, passenger arrival patterns, passenger regional approach/departure routes, place of origin/ destination, and use of airport parking facilities. Estimating Future Airport Roadway Traffic Volumes—Traditional Four-Step Approach Developing a comprehensive estimate of future traffic vol- umes on airport roadways using the traditional four-step approach involves the following: • Trip generation. Estimating the traffic volume generated by each on-airport land use during the future airportwide peak hour(s) as well as the peak hour(s) of activity for each land use. • Trip distribution. Determining the points where trips gen- erated by each airport land use enter the airport roadway network. • Mode-choice analysis. Analyzing the travel mode choice patterns of passengers and employees. • Trip assignment. Assigning the estimated traffic volumes to the on-airport and regional roadway networks. In regional planning, the third step—mode-choice analysis— is conducted using sophisticated travel demand forecasting models. These models are used to estimate future mode-choice patterns or changes in existing patterns caused by the intro- duction of new travel modes (e.g., rail service) or changes in travel time or travel cost. Such models are rarely required in an airport setting. It would be appropriate to include mode-choice analysis during the analyses of airport roadways if a significant change in the existing travel modes were anticipated (e.g., new

scheduled public bus or rail service or expansion of existing service) and if this service were expected to attract significant numbers of airline passengers or employees who currently travel by private vehicles. The three steps applicable to airport roadway operations, as well as challenges to using this approach, are described below. Estimating Traffic Volumes (Trip Generation) The key generators of airport roadway traffic are airline pas- sengers and accompanying visitors, employees working at the airport, air cargo and airmail services, airlines, in-terminal concessionaires, and other building tenants plus airport ten- ants with service or delivery needs. At most airports, the data required to estimate the volume of traffic generated by airline passengers are more readily available than comparable data for employees, air cargo, or service and delivery vehicles. Reliable statistics on existing monthly and annual volumes of airline passengers and air cargo tonnage and forecasts of airline passengers and air cargo tonnage are available for all commercial-service airports. However, as described in greater detail in subsequent paragraphs, most airport operators have limited-to-no data available on the number of employees working at their airports, or the types of air cargo shipments (e.g., overnight deliveries, small parcels, international, or other types of freight). As a result, forecasts of traffic generated by air- line passengers are often developed in substantially more detail than forecasts of traffic generated by employees, air cargo, or services and deliveries. However, traffic generated by airline passengers may represent less than half of the total (daily) vehicular traffic generated at an airport. Traffic Generated by Airline Passengers Estimating the volume of traffic generated by airline pas- sengers requires the following inputs. Number of originating and terminating airline passen- gers. Roadway traffic operations are analyzed considering the peak-hour volume (i.e., the traffic volume occurring dur- ing the busiest 60 consecutive minutes). Analyses of airport roadway traffic begin with the hourly numbers of originating and terminating airline passengers (or preferably the num- bers occurring in 15-minute increments). Originating and terminating airline passenger numbers (rather than enplaned and deplaned passenger numbers) are used to generate traf- fic volumes because these volumes exclude those passengers transferring between flights. Analyses of hour-by-hour airline passenger numbers indi- cate when the largest numbers of originating passengers, ter- minating passengers, and total passengers (originating plus terminating) arrive at, or depart from, the airport. Separate analyses of these three peak periods (originating, terminating, and total) are required because peak periods of demand on some roadway segments coincide with the originating passen- ger peak periods (e.g., the departures curbside area), and some coincide with the terminating passenger peak periods (e.g., the arrivals curbside area). The total peak period traffic volume may not coincide with the peak period of either the originating or terminating passengers, but may instead reflect the busiest overall period at the airport (e.g., the hour with the largest traf- fic volumes on the airport entry and exit roadways). At airports with significant numbers of connecting pas- sengers, the peak hours of airline passenger activity may not correlate with the peak hour of roadway traffic volumes. For airports with multiple terminals or multiple large concourses, it may be necessary to gather these hourly data for each termi- nal or each concourse. Existing originating and terminating airline passenger num- bers are available through the Origin-Destination Survey of Airline Passenger Traffic, Domestic, an online database pub- lished by the FAA, which is based on a 10% sample of all air- line tickets collected by U.S. airlines. Since foreign flag airlines are not required to participate in this ticket sample, the pub- lished originating-terminating airline passenger data may underreport passenger numbers at major international gate- way airports. Future peak-hour airline passenger numbers are a function of the future flight schedules of each airline, the anticipated size of aircraft operated (i.e., number of seats), and anticipated passenger load factors. Forecasts of airline passengers can be obtained from recent airport master plans, the FAA Terminal Area Forecast (TAF) (see http://aspm.faa.gov/main/taf.asp), and other sources. Master plans may present forecasts of annual or daily airline passenger numbers, as determined using an average day of the peak month or standard busy day rate. Such forecasts may be based on the assumption (partic- ularly at small and medium commercial-service airports) that the existing relationship between peak hour and daily airline passenger numbers will remain constant through the forecast period unless a significant change in airline operations is expected. Passenger characteristics. When possible, it is helpful to disaggregate the numbers of originating and terminating air- line passengers by trip purpose and place of residency rather than just considering the total passenger numbers because air- line passenger travel patterns (e.g., vehicle occupancies, cir- culation, and mode-choice patterns) are a function of their trip purpose (business vs. nonbusiness), place of residence (local residents vs. nonresidents), and type of flight (short- haul domestic, long-haul, transborder, overseas, or other). Typically, these data are obtained from surveys of airline 18

19 passengers or from data at peer airports. For example, resident travelers are more likely to use private vehicles and park for the duration of their trips, while nonresidents are more likely to travel to the airport in rental cars or hotel/motel courtesy vehicles and not use parking facilities. Lead and lag times. Airline passenger numbers are reported by the airlines according to the time aircraft are sched- uled to depart (push away from the gate), and arrive (touch down). Since these times do not coincide with the times motorists enter and exit airport roadways, to analyze airport roadway traffic operations it is necessary to adjust these times to reflect how much time passengers arrive at the airport in advance of their scheduled flight departure times (lead time) and depart from the airport after their scheduled flight arrival times (lag time). International passengers typically have longer lead and lag times than domestic passengers (because of the 2-hour advance check-in required by most airlines and time required for immigration and customs processing), and leisure travelers typically have longer lead and lag times than business travelers (because they are more likely to have checked baggage). Typically, these data are obtained from surveys of airline passengers or from data at peer airports. Lead time data may be aggregated to form a representative distribution (some- times referred to as an earliness distribution). Similarly, a rep- resentative distribution of lag times is sometimes referred to as a lateness distribution. Travel mode choices. To convert person trips into vehicle trips, it is necessary to first determine the travel modes used by airline passengers (or the percentage of passengers using each available travel mode). Regional transportation planning often considers just two travel modes—private vehicles and public transit—whereas airport roadway planning requires consider- ation of taxicabs, limousines, courtesy vehicles, rental cars, scheduled buses, and other travel modes. As noted, travel modes are a function of trip purpose and place of residency. Airports serving a large proportion of leisure passengers have distinctly different travel-mode-choice patterns than those serving business markets. However, at most U.S. airports, 70% to 80% of all airline passengers arrive and depart in private vehicles or rental cars. Typically, fewer than 5% to 10% of all passengers use public transportation (e.g., scheduled buses or trains, or door-to-door shared ride vans). The remaining passengers typically use taxicabs, courtesy vehicles serving hotels/motels, parking facilities, rental cars, or transportation services that require prior reservations (e.g., limousines, charter or tour buses/vans). Table 3-1 presents the Los Angeles (a) San Diego (b) Tampa (c) Salt Lake City (d) Typical vehicle occupancy (number of people) Private Vehicles Curbside 42.4% 25.5% 36.3% 27.0% 1.2 Short-term parking 4.4 17.0 8.5 1.3 Long-term parking 2.5 7.0 1.3 Off-airport parking (e) 8.3 10.0 19.5 4.5 1.3 Subtotal (private vehicles) 54.8% 55.0% 55.9% 47.0% Rental cars 11.4 19.1 36.9 35.0 1.4 Subtotal 66.2% 74.1% 92.8% 82.0% Commercial Vehicles Taxicabs 9.3% 7.3% 2.3% 1.5% 1.5 Limousines 2.0 1.3 -- 2.0 1.5 Door-to-door shuttles 10.0 9.5 2.0 4.0 Hotel/motel courtesy vehicles 5.1 5.8 3.3 10.5 2.6 Public transit 4.1 1.0 0.3 0.5 5.0 Charter/other bus 3.0 1.0 1.4 1.5 15.0 Subtotal (commercial vehicles) 33.5% 25.9% 7.3% 18.0% Total 100.0% 100.0% 100.0% 100.0% (a) Applied Management and Planning Group, 2006 Air Passenger Survey: Final Report. Los Angeles International Airport, December 2007 (b) Jacobs Consultancy, Interim Report 1: San Diego County Regional Airport Authority. Destination Lindbergh, December 2008. (c) http://www.tampaairport.com/ground_transportation/transit_survey_presentation.pdf. (d) HNTB, Landside Report, Salt Lake City International Airport, December 2002. (e) Passengers typically arrive at the curbside in courtesy vehicles. Source: LeighFisher, July 2009, based on the documents noted above. Table 3-1. Typical vehicle mode choice and occupancies at selected airports— originating airline passengers.

mode-choice patterns for typical large-hub airports. These data were obtained from recent studies prepared for Los Angeles, Salt Lake City, San Diego, and Tampa International Airports. Using the format shown in Table 3-1, some airline passengers are counted twice (e.g., a private vehicle driver who parks in an economy lot and rides a courtesy vehicle or a rental car customer who also uses a courtesy vehicle). Vehicle occupancies. Vehicle occupancies (the number of passengers per vehicle) are used to translate or convert “person trips” by travel mode into vehicle trips. When analyzing airport roadways, vehicle occupancies represent the number of airline passengers in each vehicle (i.e., excluding visitors accompany- ing airline passengers or the drivers of commercial vehicles). Typically, these data are obtained from surveys of airline pas- sengers (for single-occupancy vehicles, such as private vehicles, taxicabs, and limousines) or from visual observations for multiparty vehicles, such as courtesy vehicles, buses, and vans. The average occupancy of private vehicles operating on air- ports is higher than the average occupancy of private vehicles operating on public streets (particularly during commute hours) because vehicles on airports are typically transporting a group of airline passengers rather than just a single occupant. On-airport traffic circulation patterns. The locations on an airport where motorists begin or end their trips and the paths they follow vary according to their choice of travel mode (and parking facilities), and the on-airport roadway network configuration. Airline passengers follow numerous travel paths on an airport. For example, a private vehicle driver may enter an airport and then do one or more of the following: • Go directly to the enplaning (or deplaning) curbside area and then immediately exit the airport (e.g., a motorist drop- ping off an airline passenger who does not park), or recircu- late and return to the curbside (e.g., a motorist attempting to pick up a passenger and who was not allowed to remain stopped at the curbside). • Go first to a cell phone waiting area then proceed to the deplaning curbside to pick up an arriving airline passenger and then immediately exit the airport. • Go directly to a parking facility and park for the trip’s dura- tion (e.g., a long-term parking patron). • Go directly to the curbside area, drop off passenger(s), and then continue to a parking facility and park for the trip’s duration (e.g., a long-term parking patron). • Go directly to a parking facility, accompany a passenger into the terminal (or greet an arriving passenger at the baggage claim area), and then exit the airport (e.g., a short-term parking patron). • After landing at the airport, a passenger could go directly to a parking facility, retrieve his/her vehicle (which has been parked for the trip duration), drive back to the terminal to pick up passengers, and then exit the airport (e.g., a long- term parking patron). Similarly, rental car customers may go to the curbside area before they drop off rental cars or after they pick up rental cars. Commercial vehicle drivers may drop off customers, wait in a holding area, and then recirculate back to the terminal to pick up additional customers. Table 3-2 presents the travel paths and proportion of airline passengers using these paths for a typical large-hub airport. Medium- and small-hub airports have similar patterns, but at these airports there may be greater use of private vehicles and less use of taxicabs, limousines, courtesy vehicles, and public transit vehicles. Again, these data are typically obtained from surveys of airline passengers. Peak-hour factors. Airport roadway traffic is not uni- formly distributed over a typical peak hour or other peak period. At small airports in particular, much larger volumes of traffic may occur during one 15-minute period than during the preceding or subsequent 15-minute period. Peak-hour (adjustment) factors are used to translate nonuniform flows into equivalent hourly flows to allow for the analyses of road- ways exhibiting such nonuniform peaks. (This translation is required because roadway capacities are defined and analyses of roadway operations are performed using vehicle volume per hour.) These peak-hour factors can be determined from airport roadway traffic surveys or indirectly from analyses of airline schedules. Traffic volumes generated by airline passen- gers can be estimated by the following: • Multiplying the number of originating (or terminating) airline passengers during the peak 60-minute period times the percentage of passengers selecting each travel mode, adjusted using lead (or lag) times, and • Dividing each volume by the corresponding vehicle occu- pancy, taking care not to double count the same passen- gers (e.g., those in courtesy vehicles transporting parking patrons). Exceptions are required for vehicles that may oper- ate on a scheduled basis rather than in direct response to pas- senger demand (e.g., courtesy vehicles and scheduled buses). Regression equations that correlate vehicle trips generated to airline passengers to acres of airport property or other meas- ures are provided in Intermodal Ground Access to Airports: A Planning Guide, the ITE Trip Generation Handbook, and other reference documents. Traffic volume estimates at commercial- service airports developed using such equations are not con- sidered reliable because of the significant differences in the characteristics of each airport, including differences in airline activity peaking patterns and volumes; airline passenger demo- graphics (e.g., trip purpose, place of residency, travel mode 20

21 preferences); passenger circulation patterns on and off the air- port; airport layouts; the availability of parking, public transit, and commercial ground transportation services; and other fac- tors influencing traffic volumes. Traffic Generated by Visitors The volume of traffic generated by visitors accompanying departing airline passengers (i.e., well-wishers) and arriving airline passengers (i.e., meeters and greeters) can be deter- mined by establishing the average number of visitors accom- panying each airline passenger or group of airline passengers. The number of visitors accompanying a passenger is a func- tion of airline passenger trip destination/purpose and the demographics of the local community. For example, a greater number of visitors is expected to accompany airline passen- gers traveling overseas for leisure purposes than those accom- panying business passengers traveling on domestic flights. In some cities, passengers are greeted by a large extended fam- ily group, rather than one or two persons. Typically, visitors either (1) use only the curbside areas, (2) park (for a short period) while they accompany the airline passenger group to/from the terminal building, (3) park (for a short period) in a parking lot (or cell phone lot) and, having met the passenger in the terminal building, return to their vehicle, drive to the curbside area to pick up the passenger, and then exit the air- port, or (4) drop off passengers, park, and then return to the terminal to accompany the passengers to/from the gate (e.g., a passenger with special needs, such as an unaccompanied minor or a disabled passenger). The latter pattern (drop off and then park) has become less prevalent since 2001, because visitors are prohibited from accompanying an enplaning pas- senger to an aircraft gate or greeting a deplaning passenger at a gate. Similar to the travel times for airline passengers, visitor travel times shift from the scheduled aircraft departure and arrival times. (See Figure 3-1.) By far, most visitors travel to and from an airport in private vehicles. They rarely (i.e., less than 5%) use public transportation or other travel modes. Traffic Generated by Employees Estimating the volume of traffic generated by airport employees requires the following inputs. Volume of employees and their work schedules. On an average day, more than 10,000 people work at many large-hub airports and more than 1,000 people work at typical medium- Table 3-2. Typical vehicle circulation patterns—originating airline passengers. Travel mode Circulation pattern Percentage Private vehicles Drop off at curb, then exit 31% Drop off at curb, then park—Hourly, remain 9 Drop off at curb, then park—Hourly, then exit 4 Drop off at curb, then park—Daily Parking 7 Drop off at curb, then park—Economy Parking 4 Direct to park—Hourly, remain for duration 4 Direct to park—Hourly, exit immediately 14 Direct to park—Daily 14 Direct to park—Economy 9 Direct to off-airport 4 100% Rental Cars Direct to rental car return 73% Drop off at curb, then rental car return 23 Direct to off-airport 4 100% Taxicabs Drop off, then exit 83% Drop off, then hold area 17 100% Source: LeighFisher, July 2009, based on data gathered at Los Angeles International, Salt Lake City International, Tampa International, and other airports.

22 Figure 3-1. Sample airport visitor lead and lag time.

23 hub airports (see Table 3-3). These people are employed by the numerous employers located on an airport, as follows: • The airport operator, including third-party contractors working for the airport operator or sponsor, if different (e.g., janitorial, parking operators, and bus operators), providing services that have been outsourced; • The airlines, including flight crew, aircraft maintenance, and other employees who may not be working in the ter- minal building; • Concessionaires and other terminal building tenants, such as rental car companies and the operators of newsstands, restaurants, and other retail establishments; • Government agencies, including (at U.S. airports) the FAA, TSA, Customs and Border Protection, Immigration and Customs Enforcement, U.S. Postal Service, and (at some airports) the military; • Air cargo shippers and forwarders; • Fixed-base operators; and • Construction contractors, including construction workers and subcontractors. Airport-based employees, particularly those employed by the airlines and cargo handlers, work unusual hours, because all commercial airports operate 365 days per year, and many operate 24 hours per day. Typically, the arrival and departure hours of employees at an airport do not coincide with regional commute hours or with an airport’s peak enplaning or deplan- ing hours. For instance, major shift changes for airline employ- ees often occur between 5 A.M. and 6 A.M. and between 2 P.M. and 3 P.M. Another complicating factor is the presence of flight crews, who may only travel to/from the airport a few days per month. The trips made by flight crews at an origin-destination (O&D) airport are sporadic, but while on an assignment, they become like passengers at destination airports—requiring courtesy vehicle service or flight crew transportation services (i.e., chartered vans). Generally, employers are required to report the total num- ber of their employees requiring security badges, but do not report the number of employees working on each shift, the starting/ending times of each shift, or the travel modes used by their employees. Other than at airports with transportation management programs or ride-share promotional programs, few airport operators have accurate data indicating the num- ber of individuals working at the airport at any given time of day or the travel modes used by these individuals. Surveys of the employers located on an airport are neces- sary to determine the number of people working on the air- port, their work schedules, travel modes, and circulation patterns. Without such data (or traffic surveys conducted at Table 3-3. Number of employees at selected airports. Airport Hub size Total employees (a) Parking permits Estimated average daily employees (b) Boston-Logan International Large -- -- 14,600 Bush Intercontinental/Houston Large -- -- 14,406 Chicago O’Hare International Large -- -- 40,000 Dallas/Fort Worth International Large 28,654 -- -- Denver International Large -- -- 17,400 Fort Lauderdale-Hollywood International Large 14,000 -- 4,700 John F. Kennedy International Large 20,000 7,920 -- Lambert-St. Louis International Large -- -- 19,000 Las Vegas McCarran International Large -- -- 8,000 Los Angeles International Large -- -- 40,000 Phoenix Sky Harbor International Large 22,000 16,019 8,000 Salt Lake City International Large -- -- 13,026 San Diego International Large -- -- 3,000 San Francisco International Large 12,500 -- -- Seattle-Tacoma International Large -- -- 11,375 Tampa International Large 6,000 -- -- John Wayne (Orange County, CA) Medium -- -- 1,000 Mineta San Jose International Medium 4,750 -- -- Oakland International Medium -- -- 10,500 Omaha Eppley Airfield Medium -- -- 2,500 Portland International Medium 14,500 -- 5,000 Sacramento International Medium -- -- 1,500 (a) Includes badged and unbadged. (b) Number of people working at the airport on an average day. Source: LeighFisher, based upon information provided by individual airport operators.

the entry/exit to employee parking lots), it is difficult to deter- mine the number and pattern of employee vehicle trips. Employee travel mode choices. As noted, little data are available describing the travel modes used by employees on an airport. Data presented in ACRP Report 4: Ground Access to Major Airports by Public Transportation (2008), indicate that, at 14 airports for which data were available, about 98% of all employees working on the airport arrive and depart in private vehicles (with the exception of Boston-Logan, Chicago O’Hare, and Denver International Airports). Employee reliance on private vehicles is a result of (1) employees working nontraditional hours that do not co- incide with the operations or the schedules of public trans- portation, (2) employees residing in locations not well served by public transportation (i.e., outside the central business district), (3) employees working in locations outside of the terminal area that are not well served by public transporta- tion, and (4) the availability of free or very-low-cost employee parking on airport property. One indicator of the number of vehicles driven by employ- ees on an airport is the number of parking permits or iden- tification badges issued by the airport operator to these individuals. For example, in 1996, it was determined that 61% of the employees who were issued security badges at Los Ange- les International Airport had also been issued parking permits. The surveys indicated that, on a typical day, 29% of all employ- ees were absent due to staff schedules, vacation, illness, or working away from the office. Of those employees traveling to work on a typical day, it was determined that 64% drove alone, 33% participated in a ride-share program, and 3% rode public transit, biked, or walked. The average vehicle occupancy for those individuals traveling to work at Los Angeles International was 1.38 employees per vehicle. Because most of the large employers operate multiple shifts, about 25% of the daily employee-generated vehicle trips occurred during a single hour. These data are similar to those reported at Boston- Logan International Airport, where about 40% of all employ- ees are absent on a given weekday and about 25% of those working on a given day arrive between 6 A.M. and 10 A.M. Employee circulation patterns. The use of regional access roads and airport access roads by on-airport employees can be estimated by determining the minimum time path or mini- mum cost path between their places of residence and place of employment. Place of residence data, summarized at a zip-code level, can be obtained from parking permit applications or from databases of airport-issued security badges. The minimum travel routes between these locations and points of access to the airport can be determined using regional planning mod- els or by planners familiar with the regional highway network. Future employment and employee work schedules. Forecasts of employment and employee trips tend to be impre- cise because reliable estimates of future employment generally are not available and changes in future employment do not correlate well with changes in airline passenger numbers. His- torically, planners have estimated future employment assum- ing that the rate of growth in employment represents the average of the rate of growth in airline passenger and aircraft operations numbers. However, anecdotal information suggests that this assumption is no longer correct because the airlines appear to be reducing their numbers of employees in order to improve productivity levels and reduce costs. For example, the increasing share of passengers who obtain their boarding passes via the Internet or check their bags using electronic tick- eting kiosks has reduced the need for ticket counter agents. It is suggested that additional research is required to develop methods for estimating the volume of traffic generated by employees on airports. Sample results. Using the steps presented above, the employee trip generation rates presented in Table 3-4 were developed as part of the Los Angeles International Airport Master Plan Update. These data are presented as an example of how employee trip generation rates can vary for a day or over specific hours, and this example is not intended as a suggested proxy for another application. Traffic Generated by Air Cargo Air cargo (including airmail) traffic includes the trucks transporting the cargo, the private vehicles driven by the employees in the air cargo terminals, and customer trips. This traffic is generated by air cargo facilities (cargo terminals) located away from the passenger terminal area, freight con- solidators or forwarders, and small package deliveries made directly to the terminal area. It is recommended that the volumes of trips generated by trucks, delivery vans, and air cargo employees be estimated separately. Employee vehicle trips are the largest component of the traffic generated by an air cargo facility (over 70% of the total traffic volume, according to surveys conducted at Memphis and Los Angeles International Airports and other locations). The volumes of truck and delivery van trips generated by an air cargo facility (i.e., the trip generation rate) are unique to an individual airport and not transferable to other airports. The two measures (or dependent variables) related to air cargo that are most readily available—air cargo tonnage and the size of air cargo buildings—are not reliable indicators of the volume of cargo-related truck or total vehicle trips, largely because there are many different forms of air cargo service, 24

25 including integrated cargo handlers, all-cargo or heavy freight carriers, as well as import, export, and shipments that require special handling (e.g., flowers or fresh fish). Each form of air cargo may generate a different number of truck trips, operate at different truck arrival/departure times, and use different vehicle sizes. For example, a local overnight delivery service operation might have multiple tractor-trailers picking up and drop- ping off containers, as well as dozens of local single-unit deliv- ery vehicles distributing packages locally. Conversely, a large import/export freight operation may only generate a few tractor-trailer trips. Thus, although airport operators have reliable statistics on air cargo tonnage transported, tonnage is not a reliable indicator of the volume of truck trips because the volume of trips is a function of the type of cargo service and freight activity, not cargo tonnage (or the size of the air cargo terminal). Sample results. Although not considered applicable to all airports, the data in Table 3-5, developed for Los Angeles Inter- national Airport, present the estimated vehicle trips generated by different cargo facilities (including employee trips) per ton of air cargo. Data from Chicago O’Hare International Airport, circa 2004, indicate that a general-purpose cargo facility generated about 0.13 daily truck trips per 1,000 annual cargo tons. As noted, air cargo is transported by a wide variety of cargo shippers, each having different trip generation rates. Little, if any, research has been published, or documented, on air cargo trip generation. Additional research is required to develop methods for estimating the volume of traffic generated by air cargo terminals at airports and the employees working in these terminals. Traffic Generated by Service and Delivery Vehicles Service and delivery vehicles include those vehicles (1) bring- ing goods and materials (other than air cargo) to/from termi- nal building loading docks, consolidated warehouses, and other sites on an airport, (2) transporting individuals performing air- port maintenance and construction, (3) being used by airport police, fire, and emergency response staff, and (4) making trips not directly generated by airport passengers, employees, or air cargo. At most airports, little to no data are available on the current volume of service, delivery vehicle trips, or the activi- ties generating these trips (i.e., the extent of goods and material deliveries, trash removal, emergency responses, or construction deliveries and traffic). Generally, no data are available to guide estimates of the future volume of service/delivery vehicle trips, or the extent of future activities generating these trips. Additional research is required on this topic. Table 3-4. Example of vehicle trips per employee working at Los Angeles International Airport. Table 3-5. Estimated airport cargo trips per daily cargo tonnage at Los Angeles International Airport. Employee trip generation rate (vehicle trips per employee) Daily Morning peak (8 A.M. to 9 A.M.) Airport peak (11 A.M. to 12 P.M.) Afternoon peak (5 P.M. to 6 P.M.) Inbound 0.59 0.15 0.03 0.01 Outbound 0.59 0.01 0.03 0.15 Source: Leigh Fisher Associates, January 1996, using Los Angeles World Airports' ride-share database representing a typical weekday, Los Angeles International Airport Master Plan—Phase I, On-Airport Existing Transportation Conditions. Daily Facility peak hour Commuter peak hour trips (in Morning Afternoon Morning Afternoon Cargo shipper and out) In Out In Out In Out In Out International airline 25.2 0.39 0.13 0.19 0.29 0.23 0.13 0.16 0.16 Domestic airline 6.9 0.21 0.20 0.30 0.18 0.17 0.08 0.17 0.13 Overnight delivery service 3.0 0.30 0.24 0.77 0.27 0.30 0.03 0.55 0.26 Source: Leigh Fisher Associates, January 1996. Los Angeles International Airport Master Plan— Phase I, On-Airport Existing Transportation Conditions.

Traffic Generated by Other Airport Land Uses Other land uses commonly found at public airports include general aviation/FBO facilities and military bases. At most commercial-service airports, these other land uses do not gen- erate significant volumes of traffic during the peak hours for the airport or regional highway network. When the analysis is focused on the airport terminal area and primary airport access roadways, the traffic volumes generated by these land uses are often ignored or considered to be “background” traffic and combined with that of service/delivery vehicles. Traffic volumes generated by general aviation are a function of the number of general aviation aircraft operations, and the type of aircraft (business jets, air taxis, or small propeller aircraft). Traffic volumes generated by military bases vary according to the type of base and its function. Traffic volumes generated by nonaviation land uses that are not related to airport or aviation activity (e.g., industrial parks or large retail centers) can be estimated using the ITE Trip Genera- tion Manual. Traffic Generated by Nonairport Vehicles Using Airport Roadways Vehicles not related to the airport or airport land uses may use airport roadways as a shortcut to bypass congestion or delays on the regional roadway network. This traffic, commonly referred to as cut-through traffic, adds to airport roadway requirements and contributes to airport roadway congestion. Cut-through traffic occurs at airports having multi- ple entrance and exit points (e.g., Dallas/Fort Worth, Phoenix Sky Harbor, and Washington Dulles International Airports, and Bush Intercontinental Airport/Houston) and where the roadway network configuration allows nonairport traffic to share the airport roadways with airport-generated traffic. Most airport operators discourage such cut-through traffic. Determining the volume or proportion of existing cut- through traffic may require recording and matching the license plates or electronic toll tags of vehicles entering and exiting the airport at all major airport entry and exit points (i.e., a license plate matching survey or toll tag survey). It is not possible to identify cut-through traffic volumes using simple traffic volume counts. Estimating the volume of future cut-through traffic requires an understanding of future regional land uses and expected regional traffic patterns/travel times. The volume of nonairport traffic using airport roadways is a function of the volume of traffic on the regional roadways, and the travel-time savings these vehicles would experience if they were able to use airport roadways as a shortcut. These time savings can be determined by comparing the travel times via airport roadways and on alternative routes, knowing the forecast congestion and travel times on these routes as forecast by regional travel models or other sources. Off-Airport Origin and Destination Points (Trip Distribution) Some non-hub and small-hub airports have single entry/exit points. At these airports, all vehicles enter and exit via one roadway. The regional approach and departure vehicle distri- butions may be required to determine the proportion of left- turn, right-turn, and trough traffic at the intersection of the airport roadway with the regional highway network. Many airports have multiple entrance/exit points—one serving the terminal area and separate entrances/exits for air- craft maintenance centers, general aviation terminals, military bases, or other land uses. Although the volume of traffic using each entrance/exit can often be determined by the land use(s) served by the specific entrance/exit, large airports may have multiple connections to the regional roadway system, where the use of each is determined by regional travel patterns (or a combination of regional travel patterns and the on-airport destination). For these large airports with multiple connections to the regional roadway system, it is necessary to know the routes drivers follow when traveling to and from the airport in order to analyze (1) the intersections or junctions of the airport access roadways and regional roadway network, (2) traffic volumes on airport roadways associated with specific connec- tions to the regional roadway network, and (3) the effect of airport traffic on the regional roadway network. The routes drivers follow are a function of where they enter airport prop- erty and their on-airport destinations. These locations (or the distribution of these locations) are a function of airline pas- senger trip purpose, place of residency, regional land use pat- terns, the regional highway network, existing and forecast roadway congestion/travel times, the availability of public transit, and other factors. At airports having multiple entry/exit points serving the ter- minal area (or other major land use), drivers typically select the most convenient entry/exit point, which generally implies the point that minimizes travel time. It is possible to esti- mate the proportion (and thereby the volume) of vehicles using each entry and exit point by determining (1) the actual loca- tions where motorists (including airline passengers, visitors, and employees) begin their trips to the airport (or end their trips from the airport) or the distribution of these locations, and (2) the most logical routes used by motorists from each of these origin or destination points. At many airports, fewer than 30% of all trips begin/end in the downtown area, with the remainder arriving from or going to places of residency and employment distributed throughout the region. A planner familiar with the regional 26

27 highway network can determine the most likely routes from the primary regional origin and destination points. In addition, these data (or trip distributions) can be obtained from surveys of airline passengers or, when such data are not available, from the local metropolitan planning organization, which can pro- vide information on future distributions of places of residence and employment, a description of the future regional trans- portation network, and the likely travel paths or approach/ departure distributions. Assigning Traffic Volumes to the Roadway Network (Trip Assignment) Assigning the traffic volumes generated by airline passen- gers, visitors, employees, air cargo, and service/delivery vehi- cles to the on-airport roadway network requires information as to (1) where these vehicles enter or exit the airport, (2) their final and interim destination or origination points on the airport, and (3) the routes or paths available to these vehicles. • Airport entry and exit points. The methodology for deter- mining traffic volumes entering and exiting an airport at specific locations is provided earlier in this chapter (see Esti- mating Traffic Volumes [Trip Generation]). • Origin and destination points on the airport. The method- ology for determining the volumes of trips associated with specific on-airport origins and destinations is also provided in the previous section on Estimating Traffic Volumes (Trip Generation). • Travel paths. Typically, on a regional roadway network motorists can select from several alternative travel paths. Thus, a sophisticated traffic assignment procedure is required to allocate these vehicle trips among the available travel paths (i.e., to assign the vehicle trips to the regional roadway network) and, if desired, allocate trips to alterna- tive routes, as primary routes become congested and travel times decrease. In comparison, on an airport, there is gen- erally only a single logical travel path available for airline passengers and visitors, employees, and air cargo vehicles. Thus, the traffic assignment process is much simpler at airports. At most airports, there is only one travel path available between the airport entry and exit points and the primary origin/destination points. For example, at most airports, there is only one route connecting the airport entrance/exit and the terminal curbside areas, public parking areas, or rental car ready/return areas. Exceptions include those airports having several entrances/ exits used by airline passengers, or having multiple terminal buildings served by separate roadways. Some large airports provide internal bypass roads allowing motorists to avoid slow moving traffic at curbsides or other areas of potential congestion. Generally, at an airport, most motorists follow the guide signs directing them to the major on-airport destinations. Furthermore, most motorists will follow the prescribed routes even if they become congested, and typically deviate to a dif- ferent route only if directed to do so by a traffic control offi- cer. Most employees and service vehicle drivers follow the quickest route, unless they are prohibited from using specific roads, or tolls or fees are associated with the use of specific routes. The travel paths of originating airline passengers can be determined using the information presented in Table 3-1 (revised for the specific characteristics of the airline passengers and airport being analyzed), and the travel paths of terminat- ing airline passengers can be determined using similar infor- mation. As noted, care must be taken when assigning trips made by passengers who use multiple travel modes (e.g., those who park in a remote parking lot and also use a courtesy vehi- cle) or multiple legs (e.g., those who go to the curb and then to parking). For example, assuming that 100 vehicle trips per hour are generated by originating airline passengers at an airport; 65% of these trips are generated by private vehicles; 30% of those private vehicles go to the curb and then go to parking, where they remain for their trip duration; and 80% arrive from the east and 20% arrive from the west, these assumptions result in 20 vehicle trips by private vehicles using both the curb and daily parking (100 × 65% × 30%), of which 16 vehicles enter from the east and 4 enter from the west. The trip assignment process for airport roadways requires (1) repeating this calculation for every combination of travel mode, circulation path, and regional approach/departure path, (2) assigning these vehicle trips to the corresponding roadway links, and (3) finally determining the sum of all vehicle trips assigned to each roadway link. The sum of the vehicle trips on each roadway link represents the estimated traffic volume on that link. Travel forecasting software or spreadsheet analyses are frequently used to perform this repetitive process, particularly when traffic forecasts are being prepared for large airport roadway networks. The use of these methods allows planners to readily test the implica- tions of alternative assumptions regarding mode choice, travel paths, or airline passenger activity patterns, as well as saving time and effort. Challenges with Estimating Roadway Traffic Volumes As noted, several challenges are associated with estimating roadway traffic volumes—either existing or future—using the traditional four-step travel forecasting techniques. Key

challenges encountered by most airport operators include the following. Lack of Data on Airline Passengers Most airport operators do not conduct regular surveys of the travel modes used by airline passengers, the occupancies of vehicles transporting airline passengers, their lead and lag times, or their on-airport circulation patterns (e.g., the percent using parking or curbside areas). It is estimated that fewer than 20 U.S. airport operators regularly conduct surveys of the travel modes and circulation patterns of airline passengers and have access to current data. Lack of Data on Hourly Passenger Volumes Many airport operators do not have accurate data on hour- by-hour originating/terminating airline passenger numbers. At many airports, for planning purposes, hourly airline passenger numbers are calculated using (1) reported aircraft arrival and departure schedules, (2) aircraft sizes (and corresponding seat capacities) to determine the number of available seats per hour (or other time increment), (3) assumed load factors (by air- line)—the portion of seats occupied by passengers, and (4) the assumed portion of originating or terminating passengers (by airline). A minor difference in the estimated load factor or the proportion of enplaned/deplaned passengers in the peak hour can lead to significant differences in the numbers of peak-hour passengers. Furthermore, although planners recognize that air- craft load factors vary throughout the day and by day of the week, typically, a single load factor is applied to all aircraft of a given airline. Similarly, while the percentage of passengers who originate or terminate at an airport may vary signifi- cantly throughout the day, typically only a single originating/ terminating factor is applied to all passengers of a given airline. Lack of Data on Airport Employees As previously noted, most airport operators have little or no data regarding the numbers of employees reporting to work on a daily basis, and less data on the hour-by-hour arrival/departure patterns and travel modes used by these employees. Few, if any, airport operators have forecasts of future employment that are considered to be as reliable as the available forecasts of airline passengers. Lack of Data on Air Cargo and Service/Delivery Trips As noted earlier, additional research is required on air cargo and service/delivery vehicle trips. At most airports, little data are available on the existing numbers of trips generated by these land uses and no reliable method exists for forecasting future trips. Effort Needed to Gather Required Data Comprehensive surveys of originating and terminating air- line passengers can be costly and time consuming to plan, authorize, and conduct, with several months required to review and summarize the resulting data before they are available for release to others. Resulting Accuracy As noted, forecasts of the traffic volumes generated by air- line passengers are often prepared in substantially more detail than forecasts of traffic generated by employees, air cargo, or service/deliveries. However, although traffic generated by airline passengers may account for over 70% of the traffic during the peak hour, it typically represents less than half of the daily traffic generated by an airport. The costs and time required to gather the airline passenger data needed to fore- cast airline passenger vehicle trips should be compared with the benefits (i.e., anticipated level of accuracy). Estimating Future Airport Roadway Traffic Volumes— Alternative Approach An alternative approach to estimating future airport road- way traffic volumes involves determining existing traffic volumes on each roadway segment (or major segments) and applying a growth factor to the peak-hour volume to repre- sent future conditions. This alternative approach is com- monly called the “growth factor method.” It is suitable for quick analyses of airport curbside and terminal area roadway operations for planning purposes. Compared to the four- step forecasting approach, this approach can be applied rela- tively quickly and inexpensively. The growth factor method requires (1) determining the existing peak hour(s) roadway traffic volumes on each roadway segment or major segments, (2) developing growth factors, and then (3) multiplying the existing peak roadway traffic volumes by the selected growth factor to develop an approximation of future conditions. Growth Factor Method for Estimating Future Traffic Volumes A growth factor is the ratio between traffic volumes in the current peak hour and in the peak hour to be analyzed. A growth factor can be based on the ratio of the forecast total annual airline passenger numbers (enplaned plus deplaned passengers) for the future year to be analyzed to the equivalent 28

29 existing airline passenger numbers. Seasonal growth factors can be developed to adjust for peak-month traffic operations using data commonly available at most airports. For example, seasonal factors can be developed using the ratio of parking revenues (or, preferably, public parking transactions) during the peak month to the revenues during the current month or the ratio of month-to-month airline passenger numbers. Challenges with Use of the Growth Factor Method The major challenge with using the growth factor method is that it is relativity simplistic. This method is based on the assumption that existing patterns of activity and circulation will remain unchanged throughout the forecast period. This method also may not account for changes that may result from • New land uses on or near the airport that could affect the paths that motorists follow when entering or exiting the airport. • Changes in choices of travel modes, parking facilities, or circulation paths that may result from new or improved public transportation services, changes in parking facilities or parking rates, or increases or decreases in the propensity of motorists to use curbside roadways. • Changes in the proportion of airline passengers during the future peak month, peak day, or peak hour, although these changes could be compensated for by adjusting the growth factor appropriately. For example, if the peak hour is expected to account for a smaller proportion of daily traf- fic due to anticipated changes in airline schedules or a “flat- tening” of the peak due to increased traffic volumes, the growth factor could be adjusted accordingly. • Changes in the roadway network on or near the airport. For example, the construction of a new major regional highway may affect how vehicles approach the airport and turning movement patterns at the airport entry/exit. Sim- ilarly, a new or modified airport roadway could alter inter- nal traffic circulation and merging or weaving patterns on the airport.

Next: Chapter 4 - Analyzing Airport Terminal Area Roadways »
Airport Curbside and Terminal Area Roadway Operations Get This Book
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TRB’s Airport Cooperative Research Program (ACRP) Report 40: Airport Curbside and Terminal Area Roadway Operations includes guidance on a cohesive approach to analyzing traffic operations on airport curbside and terminal area roadways.

The report examines operational performance measures for airport curbside and terminal area roadway operations and reviews methods of estimating those performance measures. The report includes a quick analysis tool for curbside operations and low-speed roadway weaving area, highlights techniques for estimating traffic volumes, and presents common ways of addressing operational problems.

Appendix A, Glossary, to ACRP Report 40 is included in the printed report. Appendices B through G, are available online and listed below:

Appendix B: Bibliography

Appendix C: Summary of Terminal Area Roadway Traffic Volume Surveys

Appendix D: Summary of Curbside Roadway Characteristic Surveys

Appendix E: Summary of Focus Group Surveys

Appendix F: A Reproduction of Portions of TRB Circular 212

Appendix G: Overview of QATAR Curbside Analysis Methodology

Link to QATAR Curbside Analysis Methodology

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