CHAPTER 3

Estimating Airport Roadway Requirements

This chapter presents methods for estimating existing and future airport roadway traffic volumes or requirements. The data needed 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 traditional four-step approach commonly used by transportation 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 extensive data describing the characteristics of each of these traffic generators. 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.

3.1 Establishing Existing Airport Roadway Traffic Volumes and Patterns

Analyses of existing conditions and estimates of future conditions are based on observed vehicular activity. Details describing the volume, mix, and pattern of roadway traffic can be determined using data recently gathered for other purposes, if suitable, or by conducting special-purpose surveys. Additional information about traffic surveys can be found in the ITE Manual of Transportation Engineering Studies, ACRP Research Report 235: Guidebook for Conducting Airport User Surveys and Other Customer Research, and other references listed in the bibliography provided in Appendix B to this Guide.

3.1.1 Methods of Determining Existing Roadway Activity

The initial step in planning a special-purpose traffic survey is to determine what data—traffic volumes, roadway operations, vehicle characteristics, or other data—are required to support the planned analysis, whether analyzing existing operations or forecasting future operations. The traffic data required to support analyses of existing and future conditions include

• Traffic volumes. The volume of vehicles, including non-motorized vehicles, using a roadway or roadway segment forms the basis for analyses of traffic operations and for determining roadway requirements. Documentation of traffic volumes on all major airport roadways may be required to conduct master plans and comprehensive landside analyses, while the traffic volumes on only a few roadway segments (e.g., a curbside roadway) may be needed to conduct a more focused analysis.

  Traffic volumes are normally recorded in 15-minute increments to identify the peak period of activity on individual roadway segments. If peak airport traffic periods are known, it may be possible to record the traffic volumes during a 3-hour window that includes this peak period rather than conducting day-long, 48-hour, or 7-day surveys.

• Motorized vehicles. Most airport roadway traffic is comprised of motorized vehicles such as private vehicles, taxicabs, TNCs, shuttles, courtesy vans, and buses. As such, analyses of airport roadways—including access, circulation, and curbside roadways—focus on the volume, mix, and operations of these vehicles.
• Non-motorized vehicles. Bicycles, scooters, and other active modes typically represent a very small proportion of airport roadway traffic. While bicycles or other active modes have historically been used rarely by airline passengers or visitors, they are used by a small and increasing number of employees for their journey to work or for their last mile of travel (i.e., from a transit stop to their place of work). The ITE Manual of Transportation Engineering Studies and other sources describe best practices for conducting surveys of bicycles and other active modes.
• Pedestrians. The volume of pedestrians, such as those on the sidewalks adjacent to a terminal or crossing a curbside roadway, forms the basis for analysis of circulation needs/sidewalk capacities, crosswalk operations, and the need for grade-separated roadway crossings. Like vehicle traffic volumes, pedestrian traffic volumes are normally recorded in 15-minute increments. The surveys may also monitor the amount and types of baggage accompanying these pedestrians.
• Transit services. The number of transit riders boarding or alighting from bus or rail at an airport can often be obtained from the transit operator. Supplemental surveys may be required to determine the amount and types of baggage accompanying transit riders using an airport bus stop/rail station and whether the riders are airline passengers or employees working at the airport.
• Vehicle mix. In an airport environment, vehicle mix (or vehicle classification) refers to the portion of the traffic volume accounted for by individual modes, as defined by the type of service each mode provides (e.g., taxicab, TNC, courtesy vehicle, charter bus) and the type of vehicle used (e.g., sedan, passenger van, minibus, full-size bus). The proportion of large or heavy vehicles impacts roadway capacities and curbside operations.
• Vehicle occupancies. The number of passengers in vehicles (or vehicle occupancies) is used to determine the proportion of vehicles transporting multiple passengers (e.g., high-occupancy vehicles) and using the roadways efficiently. In theory, vehicle occupancies can be determined by observing or recording the number of passengers (excluding the driver of commercial vehicles) in passing vehicles. However, in practice, it is difficult to observe the number of occupants in a passing vehicle, particularly large vehicles, or those with tinted windows.
• Dwell times. The length of time a vehicle spends stopped in a curbside lane (or other location) while loading or unloading passengers and their baggage is referred to as its dwell time. Typically, the dwell time is defined as 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 during which the driver may be ready to depart but is prevented 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 curbside roadway operations.
• Curbside occupancies. This is the number of vehicles occupying or stopped at a curbside roadway or roadway section and is an indication of the number of double- or triple-parked vehicles and which portions of the available curbside are used by motorists. These data can be determined through observations of real-time operations or video recordings of curbside operations.
• Queue length. Queue length is the distance of, or number of vehicles in, a line of vehicles waiting to proceed along a roadway where (1) the flow rate of the front of the queue determines the average speed within the queue and (2) the rate of vehicles arriving in the queue is greater than the rate of vehicles 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 persistence, of the queue, also can be determined through observations. These data are used to support evaluations of airport roadway operations, particularly at the entries or exits of parking and other facilities.
• 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 segment having a length of 1,000 feet or more—can be used to support evaluations of airport roadway operations. Measuring 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.
• Weaving patterns. The proportion and volume of weaving traffic (i.e., traffic crossing two or more traffic streams without the aid of a traffic signal or other control device) can be determined by manual surveys of traffic entering and exiting a weaving segment or observing video recordings of a weaving segment.
• Recirculating traffic volumes. The proportion of vehicles passing the curbside or other location multiple times can be determined by recording and matching license plate numbers or other methods of identifying individual vehicles (e.g., monitoring the Bluetooth signal of mobile phones inside passing vehicles).
• Other data. Depending on the nature of the traffic operations problem being addressed, intercept and other surveys of airline passengers, visitors, and employees are used to gather data such as vehicle mode-choice patterns; passenger arrival patterns; passenger regional approach/departure routes; place of trip origin/destination; use of airport parking facilities; and, for employees, work schedules and location of places of work at the airport. ACRP Report 26 provides guidelines on the conduct of surveys of airline passengers, visitors, and employees.

The data needed to support analyses of airport roadway and curbside operations are most frequently gathered using manual surveys or automatic traffic recorders. In some communities, the required traffic volume data—especially the volumes on airport access roads or adjacent highways—can be obtained from local public works or traffic engineering departments. Increasingly, manual surveys are being supplemented by transportation analytics, with the expectation that in the near future these sources will reduce the extent of required manual traffic surveys. Examples of the data now available using transportation analytics and the potential application of these data for analyses of airport roadway operations include the following:

• Video recording. Video recordings of airport roadway traffic, after subsequent manual extraction, can furnish data on pedestrian and vehicle volumes, vehicle mix, and turning and weaving movements. Video recordings can be obtained from cameras installed temporarily to record specific roadway operations or permanently mounted airport-controlled security cameras. It is anticipated that ultimately the extraction of data will be automated, reducing the time and costs of gathering the desired information. Currently, private vendors offer data obtained from videos defining the trajectories of individual vehicles through an intersection or roadway segments, which can support roadway safety analyses and turning movement counts, among other analyses. When available, such data will be useful in analyzing curbside roadway operations.
• Bluetooth sensors. The signals emitted from the mobile telephones, smart watches, fitness devices, and other personal devices worn or carried by passengers in a vehicle, and even signals emitted by the vehicles themselves (e.g., tire pressure sensors) can be detected as vehicles pass sensors located adjacent to a roadway or other site. By matching the signals at multiple points, the speeds, travel paths, or routes of individual vehicles can be determined. It is estimated that 20% to 30% of the vehicles passing a sensor can be detected, leading to reliable samples. At airports, the use of Bluetooth sensors can help determine travel speeds (or delays) on the primary access roads and the proportion of non-airport (or cut-through) traffic using airport roadways.

• Connected vehicles. With an expected increase in the proportion of connected vehicles (i.e., vehicles capable of communicating and sharing data with roadway infrastructure and other vehicles), it will be possible to track and aggregate the speeds, routes, dwell times, turning movements, and other data obtained from individual vehicles. Currently, one vendor offers detailed data (e.g., use of seat belts and headlights, as well as vehicle paths, speeds, and points of origin and destination) obtained from vehicles equipped with General Motors’ OnStar service. It is estimated that this sample now represents less than 1% of the vehicles on the road. As the sample increases, it is expected that data obtained from connected vehicles may replace Bluetooth data because of the superior granularity and availability of the data.
• Vehicle detectors. Induction loops, video detection systems, and microwave sensors, embedded in roadway pavements or mounted overhead, produce accurate counts of traffic volumes and can detect the size/type of individual vehicles. Permanent detectors are frequently installed along major highways and at intersections by state and local transportation agencies. The resulting data are used to monitor traffic volumes, speeds, and patterns and determine hourly, daily, and annual use of roadways. Permanent detectors have been installed along the access roads of some airports (e.g., Boston Logan International Airport) to monitor traffic volumes and patterns. Temporary vehicle detectors (e.g., video or microwave sensors) are regularly used to gather traffic volume and speed data.
• Cell tower data/probe vehicles. Origin-destination data (e.g., trips from one zip code to another) are available from vendors that obtain and summarize data generated by trucks and other vehicles as they pass between cell towers. At present, these data are suitable for regional or corridor planning analyses, but they are not yet considered sufficiently granular or accurate to support analyses of airport roadway operations. FHWA provides free access to the National Performance Management Research Data Set (NPMRDS) data obtained from individual sample or probe vehicles, intended for transportation system performance management and to monitor and report congestion and freight performance. Again, these data are not yet sufficiently detailed to support analyses of airport roadway operations.
• Parking access control systems. Modern parking access control systems report the hourly (or smaller time increment) volume of entering and exiting vehicles by individual parking facility entry/exit lane or access point. At airports where many passengers and visitors park, these data can be used to analyze seasonal and daily patterns of airport roadway traffic and to identify peak periods of roadway traffic.

3.1.2 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 during the months with the largest volumes of airline passenger traffic. At many airports, 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. When it is not possible to conduct a survey during the busiest month, traffic volume data need to be adjusted to replicate peak-month conditions based on monthly airline passenger data (particularly originating and terminating passenger volumes), public parking transactions, volumes of passengers passing through security screening positions, or other indicators of traffic activity.

3.1.3 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 recording the number 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 identifying 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 seats and that surveys of the arrivals area (passenger pickup area) roadways be conducted during the 3 hours including and after the 60-minute period with the most arriving flights. The 60-minute departures and arrivals flight peaks do not necessarily coincide, as noted previously. At airports serving high volumes of connecting passenger traffic, roadway peak hours may not coincide with the airport’s busiest hours for departing and/or arriving flights. In such situations, existing vehicle data (such as commercial ground transportation trips recorded by the airport’s automatic vehicle identification system) or TSA security checkpoint screening data may be used to identify potential survey periods.

3.2 Estimating Future Airport Roadway Traffic Volumes—Traditional Four-Step Approach

Developing a comprehensive estimate of future traffic volumes on airport roadways using the traditional four-step approach involves the following:

• Step 1: Trip generation. Estimating the traffic volume generated by each on-airport land use during the future airport-wide peak hour(s) as well as the peak hour(s) of activity for each land use.
• Step 2: Trip distribution. Determining the points where trips generated by each airport land use enter or exit the airport roadway network.
• Step 3: Mode-choice analysis. Analyzing the travel mode-choice patterns of passengers and employees.
• Step 4: Trip assignment. Assigning the estimated traffic volumes to the on-airport and regional roadway networks.

In regional transportation 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 introduction of new travel modes (e.g., rail service) or expected changes in passenger travel time or travel cost. Such models are rarely required in an airport setting. A possible exception, triggering the need to analyze future travel mode-choice patterns, could be the introduction of new rail service or a major expansion of existing service, if this service were expected to attract significant numbers of airline passengers or employees who currently travel by private vehicles.

Expected increased use of TNCs, for example, does not warrant developing a mode-choice model. This is because, prior to the introduction of TNCs, those airport passengers choosing TNCs typically traveled in private vehicles, taxicabs, or shuttles, with few if any previously using public bus or rail transit. Increased use of TNCs would be expected to have a minor impact on the total number of vehicles entering/exiting the airport, but instead divert passengers from one type of vehicle to another, a level of detail not suitable for a typical mode-choice model. However, if TNCs do not pick up customers at the curbside, the roadways used by TNCs could differ from those of the vehicles they replaced.

Expected use of AVs could warrant use of mode-choice models if reliable data describing the operations and use of such vehicles were available. At the time this Guide was prepared, reliable data describing the operation and use of AVs at airports were not available. Until data gathered from observations of AVs operating in similar environments are available, it is suggested that the effort required to develop and use mode-choice models to predict the impact of AVs is not justified.

The remaining three steps, those applicable to airport roadway operations, as well as challenges to using this approach, are described in the following.

3.2.1 Estimating Traffic Volumes (Trip Generation)

The key generators of airport roadway traffic are (1) airline passengers and accompanying visitors, (2) employees working at the airport, air cargo and airmail services, airlines, in-terminal concessionaires, and other building tenants, and (3) airport tenants 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 documenting existing monthly and annual volumes of airline passengers and air cargo tonnage and forecasts of airline passengers and air cargo tonnage are available for virtually 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 at any point in time 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 airline 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 passengers requires the following inputs.

Number of Originating and Terminating Airline Passengers.

Roadway traffic operations are analyzed considering the peak-hour volume (i.e., the traffic volume occurring during the busiest 60 consecutive minutes). Analyses of airport roadway traffic begin with the hourly numbers of originating and terminating airline passengers (or preferably the numbers occurring in 15-minute increments). Originating and terminating airline passenger numbers (rather than enplaned and deplaned passenger numbers) are used to generate traffic volumes because these volumes exclude those passengers transferring between flights who do not use the airport curbsides or roadways.

Analyses of hour-by-hour airline passenger numbers indicate when the largest numbers of originating passengers, terminating 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 passenger 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 traffic volumes on the airport entry and exit roadways).

At airports with significant numbers of connecting passengers, 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 terminal or each concourse. Existing originating and terminating airline passenger numbers are available through two Bureau of Transportation Statistics products: the Airline Origin and Destination Survey (DB1B) (https://www.bts.gov/topics/airlines-and-airports/origin-and-destination-survey-data) and Data Bank 28IS - T-100 and T-100(f) International Segment Data, U.S. and Foreign Air Carriers Traffic and Capacity Data (World Area Code) (https://www.bts.gov/browse-statistical-products-and-data/bts-publications/%E2%80%A2-data-bank-28is-t-100-and-t-100f). These data are based on a 10% sample of all airline tickets collected by U.S. airlines. Since foreign flag airlines are not required to participate in this ticket sample, the published originating-terminating airline passenger data may underreport passenger numbers at major international gateway 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 (see https://www.faa.gov/data_research/aviation/taf/), 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 (particularly at small and medium commercial-service airports) may assume 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 airline passengers by trip purpose (business vs. non-business or leisure) and place of residency (local residents vs. visitors or non-residents), rather than just considering the total passenger numbers. This is because airline passenger travel patterns (e.g., vehicle occupancies, circulation, and mode-choice patterns) are a function of the passenger’s trip purpose, place of residence, and type of flight (short-haul domestic, long-haul, transborder, overseas, or other). For example, resident travelers are more likely to use private vehicles and park for the duration of their trips, while non-residents are more likely to travel to the airport in rental cars or hotel/motel courtesy vehicles and not use parking facilities. Business travelers are generally more time sensitive and less cost-sensitive than leisure or non-business travelers, which influences their choice of parking facilities, and use and familiarity with airport roadways. Typically, these data are obtained from surveys of airline passengers or from data at peer airports.

Lead and Lag Times.

Airline passenger numbers are reported by the airlines according to the time aircraft are scheduled 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 far in advance of their scheduled flight departure times passengers enter an airport (lead time) and how long after their scheduled flight arrival times passengers exit an airport (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 for international travel and the time required by passengers to clear immigration and customs processing). Leisure travelers typically have longer lead and lag times than business travelers (because they are more likely to have checked baggage and allow for an extra time buffer). 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 (sometimes referred to as an earliness distribution). Similarly, a representative distribution of lag times is sometimes referred to as a lateness distribution. The TSA reports passenger earliness distribution times (minutes before scheduled flight departure time) based on the time passengers check their baggage, which can serve as a proxy or indicator of lead time distributions.

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 consideration of taxicabs, TNCs, 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, TNCs, courtesy vehicles serving hotels/motels, parking facilities, rental cars (e.g., if the rental car facilities are remotely located), or transportation services that require prior reservations (e.g., limousines, charter or tour buses/vans). Table 3-1 presents the mode-choice patterns for airports serving Grand Rapids, Los Angeles, San Francisco, Seattle-Tacoma, and New York. 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 accompanying airline passengers or the drivers of commercial vehicles). Typically, these data are obtained from surveys of airline passengers (for single-occupancy vehicles, such as private vehicles, taxicabs, TNCs, and limousines) or visual observations for multiparty vehicles, such as courtesy vehicles, buses, and vans. The average occupancy of private vehicles operating at airports is higher than the average occupancy of private vehicles operating on

Table 3-1. Typical vehicle mode choice and occupancies at selected airports—originating airline passengers.

Note: Percentages may not total 100 due to rounding.

^a Gerald R. Ford International Airport, airport staff, based on July 2019 data.

^b Los Angeles International Airport, Draft Environmental Impact Report, September 2016.

^c San Francisco International Airport, 2016–2017 Curbside Congestion Study.

^d Seattle-Tacoma International Airport, airport staff, based on 2019 data.

^e Port Authority of New York & New Jersey, 2019 Air Traffic Report.

public streets (particularly during commute hours) because vehicles at airports typically transport a group of airline passengers rather than just a single occupant.

On-Airport Traffic Circulation Patterns.

The locations at 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 at 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 dropping off an airline passenger who does not park), or recirculate and return to the curbside (e.g., a motorist attempting to pick up a passenger who was not allowed to remain stopped at the curbside).
• Go first to a cell phone waiting area, 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 duration (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. After dropping off customers, commercial vehicle drivers may either immediately exit the airport or wait in a holding or staging 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

Table 3-2. Vehicle circulation patterns.

Source: Based on information provided by individual airport operators.

less use of taxicabs, TNCs, limousines, courtesy vehicles, and public transit vehicles and fewer short-term parking patrons, especially if there are few international passengers. Again, these data are typically obtained from surveys of airline passengers.

Peak-Hour Factors.

Airport roadway traffic is not uniformly 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 non-uniform flows into equivalent hourly flows to allow for the analyses of roadways exhibiting such non-uniform peaks. This translation is required because flow rates of vehicles per hour are used to define roadway capacities and analyze roadway operations. These peak-hour factors can be determined from airport roadway traffic surveys or indirectly from analyses of airline schedules. Traffic volumes generated by airline passengers can be estimated by the following:

• Multiplying the number of originating (or terminating) airline passengers during the peak 60-minute period by the percentage of passengers selecting each travel mode, adjusted using lead (or lag) times, and
• Dividing each volume by the corresponding vehicle occupancy, taking care not to double count the same passengers (e.g., those in courtesy vehicles transporting parking patrons). Exceptions are required for vehicles that may operate on a scheduled basis rather than in direct response to passenger demand (e.g., courtesy vehicles and scheduled buses).

Regression equations that correlate vehicle trips generated to airline passengers, to acres of airport property, or to other measures 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 considered reliable because of the significant differences in the characteristics of each airport, including differences in airline activity peaking patterns and volumes; airline passenger demographics (e.g., trip purpose, place of residency, travel mode preferences); passenger circulation patterns on and off the airport; airport layouts; the availability of parking, public transit, and commercial ground transportation services; and other factors influencing traffic volumes. Furthermore, these metrics ignore trips generated by employees, air cargo, and other on-airport land uses.

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., commonly referred to as meeters and greeters) can be determined by establishing the average number of visitors accompanying each airline passenger or group of airline passengers. The number of visitors accompanying a passenger is a function of the airline passenger’s trip destination and/or trip purpose and the demographics of the local community. For example, more visitors generally accompany airline passengers traveling overseas for leisure purposes than those accompanying business passengers traveling on domestic flights. In some cities, passengers are greeted by a large extended family 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, and, having met the deplaning passenger in the terminal building, return to their vehicle, drive to the curbside area to pick up the passenger, and then exit the airport; (4) wait in a cell phone waiting area for the arrival of a deplaning airline, drive to the curbside area to pick up the passenger, and then exit the airport; or (5) drop off enplaning 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). Similar to the lead and lag times for airline passengers, visitor arrival times at the airport can lead or lag 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-hub airports (see Table 3-3). These people are employed by the numerous employers located at an airport, as follows:

• The airport operator, including third-party contractors working directly for the airport operator (e.g., janitorial, parking operators, and bus operators) providing services that have been outsourced.
• The airlines, including flight crew, counter agents and baggage handlers, aircraft maintenance, and other employees who may not be working in the terminal building.
• Third-party service providers contracted by airlines to provide maintenance, ground handling, and other services.
• Concessionaires and other terminal building tenants, such as operators of newsstands, restaurants, and other retail establishments and rental car companies whose employees may not be working in the terminal building.

Table 3-3. Estimated number of employees at airports.

Source: Based upon information provided by individual airport operators.

^a Includes badged and unbadged.

^b Number of people working at the airport on an average day.

• 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.
• FBOs.
• 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 deplaning hours. For instance, major shift changes for airline employees 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 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 number 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 rideshare promotional programs, few airport operators have accurate data indicating the number 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 at an airport are necessary to determine the number of people working at the airport, their work schedules, travel modes, and circulation patterns. Without

such data (or traffic surveys conducted at the entry/exit to employee parking lots), it is difficult to determine 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 at an airport. Data presented in ACRP Report 4: Ground Access to Major Airports by Public Transportation (2008), indicated that, at 14 airports for which data were available, about 98% of all employees working at the airport arrived and departed 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 non-traditional hours that do not coincide with the operations or the schedules of public transportation, (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 transportation, and (4) the availability of free or very-low-cost parking for employees on airport property.

One indicator of the number of vehicles driven by employees at an airport is the number of parking permits or identification 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 Angeles International Airport had also been issued parking permits. The surveys indicated that, on a typical day, 29% of all employees 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 rideshare 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 employees 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 minimum 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 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 models, from publicly available website-based mapping programs and services, or by planners familiar with the regional highway network.

Future Employment and Employee Work Schedules.

Forecasts of employment and employee trips tend to be imprecise 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. Historically, planners have estimated future employment assuming that the rate of employment growth 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 ticketing 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 at 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

Table 3-4. Example of vehicle trips per employee working at Los Angeles International Airport.

Source: Leigh Fisher Associates, January 1996, using Los Angeles World Airports’ rideshare database representing a typical weekday, Los Angeles International Airport Master Plan—Phase I, On-Airport Existing Transportation Conditions.

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 consolidators 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 (more than 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, 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. The use of cargo facilities located at an airport may also be used for truck-to-truck transfer by overnight express carriers.

For example, a local overnight delivery service operation might have multiple tractor-trailers picking up and dropping off containers, as well as dozens of local single-unit delivery 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). ACRP Synthesis 80: Estimating Truck Trip Generation for Airport Air Cargo Activity provides a comprehensive review of this topic and the difficulty in estimating truck trips generated by air cargo activity.

Although not considered applicable to all airports, the data shown in Table 3-5, developed for Los Angeles International 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.

Table 3-5. Estimated airport cargo trips per daily cargo tonnage at Los Angeles International Airport.

Source: Leigh Fisher Associates, January 1996. Los Angeles International Airport Master Plan—Phase I, On-Airport Existing Transportation Conditions.

As noted, air cargo is transported by a wide variety of cargo shippers, each having different trip generation rates. 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) bringing goods and materials (other than air cargo) to/from terminal building loading docks, consolidated warehouses, and other sites on an airport; (2) transporting individuals performing airport 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 and delivery vehicle trips or the activities 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.

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 generate 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 and 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 non-aviation 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 Generation Handbook.

The employees of airport rental car companies shuttle returned (or dirty) vehicles to a service area where the vehicles are washed, fueled, and serviced, and then stored until they are ready to be rented to another customer. Typically, the movement of vehicles occurs securely within the rental car company’s property and does not require the use of public roadways. However, at a few airports, where the vehicle service area is located apart from the site where vehicles are returned and rented, the movement occurs on public roadways. In these instances, the shuttling of rental car vehicles should be included in estimates of traffic generated by other land uses.

Traffic Generated by Non-Airport 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 multiple entrance and exit points (e.g., Dallas/Fort Worth, Phoenix Sky Harbor, Washington Dulles International Airports, and Bush Intercontinental Airport/Houston) and where the roadway network configuration allows non-airport 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 the use of Bluetooth surveys or other survey methods. It is not possible to identify cut-through vehicles or 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 non-airport 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 those on alternative routes, knowing the forecast congestion and travel times on these routes as forecast by regional travel models or other sources.

3.2.2 Off-Airport Origin and Destination Points (Trip Distribution)

With respect to analyses of airport terminal area and curbside traffic, trip distribution refers to the proportion of airport-generated trips originating (or terminating) in each portion of the airport’s catchment area (by zip code, traffic analysis zone, cardinal direction, or other indicator) and consequently the path followed to enter and exit the airport. The paths passengers follow are a function of the travel mode they chose, where they enter airport property, and their on-airport destinations. These locations (or the distribution of these locations) are a function of airline passenger trip purpose, place of residency, regional land use patterns, the regional highway network, existing and forecast roadway congestion/travel times, the availability of public transit, and other factors.

At small airports, having a single primary access road that terminates at an intersection or interchange with a regional arterial highway, trip distribution refers to the proportion of airport-generated trips entering (or exiting) the airport from each cardinal direction and turning left, right, or through to enter or exit the airport. At airports reviewing new or expanded public transit service, analyses of passenger and employee trip distributions can indicate the volume of airport-generated trips that originate or terminate near (i.e., within walking distance of) a transit stop and comprise the likely market for transit.

Many large airports have multiple entrance/exit points—one serving the terminal area and separate entrances/exits for aircraft 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 airports with multiple connections to the regional roadway system, it is necessary to know the routes passengers and employees 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 connections to the regional

roadway network, (3) the effect of airport traffic on the regional roadway network, and (4) potential transit ridership.

At airports having multiple entry/exit points serving the terminal area (or other major land use), passengers typically select the most convenient entry/exit point, which generally implies the point that minimizes travel time. It is possible to estimate the proportion (and thereby the volume) of vehicles using each entry and exit point by determining (1) the actual locations where 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 passengers 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 or leisure destinations distributed throughout the region. A planner familiar with the regional 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 provide information on future distributions of places of residence and employment, a description of the future regional transportation network, and the likely (minimum time) travel paths or approach/departure distributions.

3.2.3 Assigning Traffic Volumes to the Roadway Network (Trip Assignment)

Assigning the vehicle trips generated by airline passengers, visitors, employees, air cargo, and service/delivery vehicles 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 at the airport, and (3) the routes or paths available to these vehicles.

• Airport entry and exit points. The methodology for determining traffic volumes entering and exiting an airport at specific locations is provided earlier in this chapter (see Estimating Traffic Volumes [Trip Generation]).
• Origin and destination points at the airport. The methodology for determining the volumes of trips associated with specific on-airport origins and destinations is also provided in the previous section, “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 alternative routes, as primary routes become congested and travel times decrease. In comparison, at an airport, there is generally 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.

As discussed earlier, 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, most motorists at an airport 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 different route only if directed to do so by a traffic control officer or, in some instances, their in-vehicle navigation system. 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 3-2 (revised for the specific characteristics of the airline passengers and the airport being analyzed), and the travel paths of terminating airline passengers can be determined using similar information. 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 vehicle) 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, and for multiple future years. The use of these methods allows planners to readily test the implications of alternative assumptions regarding mode choice, travel paths, or airline passenger activity patterns, as well as saving time and effort.

3.2.4 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 airline passengers to gather reliable data indicating the passenger’s travel modes, circulation patterns, and vehicle occupancies. Furthermore, even at those airports where passenger surveys are conducted, the surveys typically focus on enplaning passengers and gathering data during multiple hours and days with relatively few samples gathered during peak periods. Therefore, survey data may not capture mode-choice variances between departing and arriving passengers (e.g., drivers picking up arriving passengers may be more likely to use short-term parking and meet their passengers in the terminal whereas drivers dropping off departing passengers may be more likely to drop off the passengers at the curbside) nor mode-choice variances by time of day (e.g., passengers departing on early morning flights may be less likely to use public transit if transit service does not operate early enough to deliver them to the airport sufficiently ahead of their scheduled departure time).

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 airline)—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 (or peak month) can lead to significant differences in the numbers of peak-hour passengers. Furthermore, although planners recognize that aircraft load factors vary throughout the day, by day of the week, and seasonally, 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 significantly throughout the day or seasonally, 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 number of employees reporting to work on a daily basis, and less data on the work schedules, 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 airline 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 airline 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 forecast airline passenger vehicle trips should be compared with the benefits (i.e., anticipated level of accuracy).

3.3 Estimating Future Airport Roadway Traffic Volumes—Alternative Approach

An alternative approach to estimating future airport roadway 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 represent future conditions. This alternative approach is commonly 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 relatively 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, (3) adjusting the forecast growth to reflect changes in travel modes, and then (4) multiplying the existing peak roadway traffic volumes by the selected growth factor to develop an approximation of future conditions.

3.3.1 Growth Factor Method for Estimating Future Traffic Volumes

A growth factor is the ratio between traffic volumes during the current peak hour and during the peak hour to be analyzed. A growth factor can be developed by determining the ratio between (1) the forecast total annual airline passenger volumes (enplaned plus deplaned passengers) for the future year to be analyzed and (2) the equivalent existing airline passenger volumes. 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.

Using judgment, the growth factor can be adjusted to reflect changes in travel modes (e.g., anticipated future of AVs or transit services) by passengers and employees, or possible changes in trip distribution to reflect new access routes, new or improved public transit services, or regional transportation improvements.

3.3.2 Challenges with Use of the Growth Factor Method

The major challenge with using the growth factor method is that it is relatively simplistic. This method assumes that existing patterns of activity and circulation will remain generally 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 passengers and employees 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. However, as noted above, judgment or available data can be applied to the calculated growth factor to account for these changes, particularly if the changes are expected to be relatively minor.
• Changes in the proportion of airline passengers during the future peak month, peak day, or peak hour, although again 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 traffic due to anticipated changes in airline schedules or a “flattening” 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. Similarly, a new or modified airport roadway could alter internal traffic circulation and merging or weaving patterns at the airport.