National Academies Press: OpenBook

Simulation Options for Airport Planning (2019)

Chapter: Chapter 4 - Simulation Tool Application Guidelines

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Suggested Citation:"Chapter 4 - Simulation Tool Application Guidelines." National Academies of Sciences, Engineering, and Medicine. 2019. Simulation Options for Airport Planning. Washington, DC: The National Academies Press. doi: 10.17226/25573.
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Suggested Citation:"Chapter 4 - Simulation Tool Application Guidelines." National Academies of Sciences, Engineering, and Medicine. 2019. Simulation Options for Airport Planning. Washington, DC: The National Academies Press. doi: 10.17226/25573.
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Suggested Citation:"Chapter 4 - Simulation Tool Application Guidelines." National Academies of Sciences, Engineering, and Medicine. 2019. Simulation Options for Airport Planning. Washington, DC: The National Academies Press. doi: 10.17226/25573.
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Suggested Citation:"Chapter 4 - Simulation Tool Application Guidelines." National Academies of Sciences, Engineering, and Medicine. 2019. Simulation Options for Airport Planning. Washington, DC: The National Academies Press. doi: 10.17226/25573.
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Suggested Citation:"Chapter 4 - Simulation Tool Application Guidelines." National Academies of Sciences, Engineering, and Medicine. 2019. Simulation Options for Airport Planning. Washington, DC: The National Academies Press. doi: 10.17226/25573.
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Suggested Citation:"Chapter 4 - Simulation Tool Application Guidelines." National Academies of Sciences, Engineering, and Medicine. 2019. Simulation Options for Airport Planning. Washington, DC: The National Academies Press. doi: 10.17226/25573.
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Suggested Citation:"Chapter 4 - Simulation Tool Application Guidelines." National Academies of Sciences, Engineering, and Medicine. 2019. Simulation Options for Airport Planning. Washington, DC: The National Academies Press. doi: 10.17226/25573.
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Suggested Citation:"Chapter 4 - Simulation Tool Application Guidelines." National Academies of Sciences, Engineering, and Medicine. 2019. Simulation Options for Airport Planning. Washington, DC: The National Academies Press. doi: 10.17226/25573.
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Suggested Citation:"Chapter 4 - Simulation Tool Application Guidelines." National Academies of Sciences, Engineering, and Medicine. 2019. Simulation Options for Airport Planning. Washington, DC: The National Academies Press. doi: 10.17226/25573.
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Suggested Citation:"Chapter 4 - Simulation Tool Application Guidelines." National Academies of Sciences, Engineering, and Medicine. 2019. Simulation Options for Airport Planning. Washington, DC: The National Academies Press. doi: 10.17226/25573.
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Suggested Citation:"Chapter 4 - Simulation Tool Application Guidelines." National Academies of Sciences, Engineering, and Medicine. 2019. Simulation Options for Airport Planning. Washington, DC: The National Academies Press. doi: 10.17226/25573.
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Suggested Citation:"Chapter 4 - Simulation Tool Application Guidelines." National Academies of Sciences, Engineering, and Medicine. 2019. Simulation Options for Airport Planning. Washington, DC: The National Academies Press. doi: 10.17226/25573.
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Suggested Citation:"Chapter 4 - Simulation Tool Application Guidelines." National Academies of Sciences, Engineering, and Medicine. 2019. Simulation Options for Airport Planning. Washington, DC: The National Academies Press. doi: 10.17226/25573.
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Suggested Citation:"Chapter 4 - Simulation Tool Application Guidelines." National Academies of Sciences, Engineering, and Medicine. 2019. Simulation Options for Airport Planning. Washington, DC: The National Academies Press. doi: 10.17226/25573.
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Suggested Citation:"Chapter 4 - Simulation Tool Application Guidelines." National Academies of Sciences, Engineering, and Medicine. 2019. Simulation Options for Airport Planning. Washington, DC: The National Academies Press. doi: 10.17226/25573.
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Suggested Citation:"Chapter 4 - Simulation Tool Application Guidelines." National Academies of Sciences, Engineering, and Medicine. 2019. Simulation Options for Airport Planning. Washington, DC: The National Academies Press. doi: 10.17226/25573.
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25 It can sometimes be difficult to select the appropriate analytical method or simulation tool for a specific airport planning or design study. Some tools are custom designed for specific purposes, whereas others are more generic but equally as valid depending on the study. So, it is not only important to understand simulation tool capabilities but also where and how they may be used, what data and resources are generally required, and how difficult they are to apply. Using the information gained from the survey and from current industry practices, this report develops basic guidelines that airport planners and designers can use to select simulation tools. Based on the survey, the factors that organizations generally considered in selecting simu- lation tools for their planning and design efforts focus on project type (i.e., master plans or capacity and demand studies), study budget, schedule, and required resources. More than 70 percent of respondents considered these factors to be important. Simulation input data requirements and availability and output capabilities also play a significant role but are con- sidered less important. The industry and government acceptance levels as well as the level of anticipated study scrutiny and review seem to play only minor roles in the selection of simula- tion and analysis tools for studies. See Figure 10 for a comparison of the relative importance of each factor in simulation tool selection. Based on this guidance, the project type was used as the primary decision factor for selecting a simulation tool for an airport planning and design study. The simulation tool selection is then further refined using important project characteristics. The survey and current industry trends indicated a basic selection process that can be described using the following ordered criteria: 1. Project Type. 2. Desired Metrics and Simulation Inputs and Outputs. 3. Resource and Schedule Requirements. The fidelity of simulation tools used for airport planning varies significantly based on these criteria, as does the cost of the eventual construction project that is being considered. So, it is not surprising that detailed analytical and simulation models of airside operations are highly mature, given the considerable risk and cost of incorrect assessments. But, as Barnhart, Belobaba, and Odoni expressed, caution must be taken in the correct application of these models based on areas of analysis suited to the project (Barnhart et al., 2003). Looking at the different kinds of projects that typically include simulation studies, the clear majority appear to focus on capacity and demand planning. Master planning and day-by-day operational planning projects also see frequent applications of simulation tools. Figure 11 pro- vides a breakdown of simulation tool usage by project type based on survey data. However, the simulation project types also vary depending on the area of focus: airspace, airport, terminal, or ground access. Table 9 lists the most common types of projects in which simulation tools were applied by area based on survey respondents and recent literature. C H A P T E R 4 Simulation Tool Application Guidelines

26 Simulation Options for Airport Planning Figure 10. Survey results—factors considered in simulation tool selection. Figure 11. Survey results—simulation project types and usage. The guidelines presented in this report will follow these basic criteria to assist airport plan- ners and designers in selecting and applying simulation tools. The remainder of this section is organized by project type so that the reader can quickly navigate to areas of particular interest. Several matching case examples are presented for the reader to delve more deeply into simula- tion projects, requirements, and analysis metrics. Master Planning An airport master plan provides a blueprint for future operations from an operational and infrastructure point of view, including details of runway design, taxiway design, and terminal design. If the master plan is not correctly and carefully developed, airport performance can be affected for many years. The correct and appropriate use of simulation tools can significantly

Simulation Tool Application Guidelines 27 assist in informing key decision making in this regard. However, a high-fidelity and expen- sive simulation software used on a small project can easily drive project costs and schedules out of control. Likewise, a low-fidelity but cheaper tool may not be sufficiently capable of accounting for complex scenarios that require consideration on a large project. Therefore, picking the right simulation tool for the project at hand is the key factor in achieving a successful master plan. For example, for an airfield capacity study in which delay numbers are not important but simple runway throughput is needed (i.e., a general aviation airport with one runway or a proposed new runway), runwaySimulator may be an appropriate simulation tool. It can be considered a low- to medium-fidelity simulation tool, but at the same time the tool is sufficiently accurate to assess runway capacity without any ground constraints. The input requirements for runwaySimulator and other low-fidelity simulation tools are minimal and associated preparation time is hours versus days as compared with higher fidelity models such as TAAM, SIMMOD, or AirTOp (LeighFisher et al., 2012). As expected, medium-fidelity tools such as the Airport Delay Simulation Model (ADSIM) require more extensive input data to achieve greater accuracy in modeling aircraft and analysis data. Although this increases the development time for simulation scenarios, they deliver more robust and detailed results. Table 10 illustrates the use of ADSIM and the Runway Delay Simula- tion Model (RDSIM) within an initial master planning capacity study at Memphis International Airport in Tennessee. Figure 12 shows the ADSIM simulation user interface of an airfield, including runways, taxi- ways, aprons, and gates. For more complex master plans, particularly for airports within metropolitan areas, an air- space component may force the use of high-fidelity simulation tools. If a study calls for new runways, major airfield reconfigurations, or significant airspace changes, higher fidelity models such as AirTOp, TAAM, SIMMOD, or CAST Aircraft are more appropriate simulation tools. Specifically, if an environmental impact statement (EIS) or environmental impact assessment (EIA) is planned or anticipated, a high-fidelity model is the best choice. Although these simula- tion tools require the most effort and resources in terms of data processing, preparation, setup, Airspace Master planning Procedure design Future concepts TMA/TRACON impact planning Obstruction planning Macroeconomic analyses Airport/Airfield Master planning Capacity planning and design Construction and operations planning Resource planning Irregular operations planning Flight schedule evaluations Terminal Passenger Terminal passenger capacity planning Passenger/terminal process design Check-in and security checkpoint design Staff/resource planning Security threat analyses Terminal Systems Baggage system planning Bus/train/shuttle planning Ground Access and Curbside Airport road access planning Airport terminal access planning Evaluation of construction zone impacts Toll plaza analysis Pedestrian flow analysis Transit facility planning Table 9. Simulation project types by area.

28 Simulation Options for Airport Planning and calibration, they provide the necessary granularity and environmental controls to support costly decisions. As mentioned in the Chicago O’Hare International Airport (ORD) Final EIS document, the rationale for using high-fidelity models for complex master planning includes their ability to facilitate direct and real-time review of simulation models by air traffic controllers and other sub- ject matter experts (FAA, 2005). This same rationale was also a driving factor in the use of TAAM for the Philadelphia International Airport (PHL) Capacity Enhancement Project, as outlined in Table 11. The PHL TAAM simulation study also fed information to the subsequent EIA and EIS. Large hub airports across the globe have used high-fidelity simulation tools to drive invest- ment decisions for many years. As expected though, the simulation know-how, input data requirements, and time required to prepare simulation scenarios can be quite extensive. Study Purpose Capacity Enhancement Plan Update–1997 Organization Federal Aviation Administration Technical Center and Memphis-Shelby County Airport Authority Environment An example of dozens of such Capacity Enhancement Plans prepared by the FAA Technical Center and local Airport Capacity Design Teams. Airfield capacities and aircraft delays were calculated for baseline conditions (existing demand and operating procedures). Benefits of proposed improvements were measured against these baseline capacities and delays. Model Used ADSIM and RDSIM Metrics Hourly airport capacity corresponding to an average aircraft delay of 4 minutes total and average aircraft delays and costs. Resource and Data Requirements Airfield layouts, operational procedures, and rules Weather conditions Hourly, daily, and annual traffic data and mix Applicability to Airport Planning/Design Airfield (runway) capacity planning Reference ACRP 03-17: Master Plan Update, Memphis International Airport, LeighFisher, 2008, available at: http://onlinepubs.trb.org/onlinepubs/acrp/ docs/ACRP03-17_FR.pdf. P. 1-21. Table 10. Medium-fidelity airport master plan simulation case example. Figure 12. ADSIM airport simulation. Source: FAA.

Simulation Tool Application Guidelines 29 Some of the most common metrics derived from such tools are: • Capacity. • Delays. • Conflict points. • Facility utilization. Delays are often annualized as part of a CBA in which return on investment decisions can be made that measure monetary benefits of improved future capacity and efficiency against the cost of capital improvement projects. Construction Phasing Plans and Impact Studies The simulation of construction phasing plans goes hand in hand with the master planning process. As preferred alternative layouts or operational scenarios are identified, construction time and resource availability dictate when parts of the master plan layout are going to be con- structed. This generally results in a construction phasing plan in which each phase has specific impacts on airfield or terminal operations that require impact assessments. For this task, planners are likely to use the same simulation tools that were used through- out the initial master planning effort because they have been validated and represent cur- rent and future demand-driven operational scenarios that only need to be adapted. Existing master plan models are generally used and modifications are made to represent the various construction phase layouts, operational restrictions, and proposed taxi paths and gate assign- ments. Frequently, the simulation tools can also be used to optimize taxi flows and ground movements. In contrast to the master plan simulation effort, the metrics will focus more on ground opera- tions efficiency and delays than airport-level capacities and future capacity and demand issues. Although it is important to ensure that ground traffic restrictions do not starve the runways, the analysis will likely focus more on airfield delays, choke points, and demand variability. Study Purpose Philadelphia International Airport Capacity Enhancement Project Organization Philadelphia International Airport (PHL) Environment To enhance airport capacity and accommodate current and future aviation demand in the Philadelphia metropolitan area during all weather conditions Model Used TAAM Metrics Capacity, delays Resource and Data Requirements Detailed future airport layouts, including construction years DDFS (current and future), Standard Instrument Departure (SID) and Standard Terminal Arrival Routes (STARs) Taxiway flow diagram, etc. Current and future airport gate and apron usage Applicability to Airport Planning/Design Airport master planning Reference FAA Record of Decision for Capacity Enhancement Program at Philadelphia International Airport, 2010. Table 11. High-fidelity airport master plan simulation case example.

30 Simulation Options for Airport Planning Airport Capacity and Delay Studies Whereas master planning studies use purpose-built simulation scenarios to evaluate proposed airport layout changes, capacity and delay studies are commonly used to assess the impacts of future demand growth on existing or proposed infrastructure. These studies are more common and informal than the ones for master plans and typically evaluate aspects related to future airport capacity saturation as well as benefits gained from major infrastructure changes such as new runways and terminals. It is common for airport capacity and delay studies to use a series of synthetic future demand schedules to determine the capacity of a given airfield or terminal layout. They can focus on any aspect of the airfield, including runways, taxiways, gates, or the entire airfield itself. The scope of the study naturally dictates the fidelity level of the simulation tool that should be used. Runway capacity studies simply focus on arrival and departure movements on runways and can take runway dependencies, wake turbulence separation criteria, and basic runway allocation rules into consideration. Using future demand schedules, various alternative runway capacities can be determined for airfield operating configurations, including additional runways, the clo- sure of runways, or the reallocation of traffic by runway. These types of studies may best be conducted using low- to medium-fidelity simulation tools such as runwaySimulator or Airtopsoft’s runway capacity module. The use of runwaySimulator for basic airport or runway-level capacity planning is outlined in Table 12, and a basic visualiza- tion of runway operations is illustrated in Figure 13. Often, runway capacity studies are conducted as initial phases of larger airfield or airspace planning studies and they discount other airfield capacity bottlenecks. As the case study in Table 12 illustrates, runwaySimulator is a popular tool for making simple airport capacity pre- dictions across multiple operating configurations, weather conditions, and environments. When taxiway, apron, or gate capacity is a perceived problem, the scope of the simulation effort naturally increases to a point where a more detailed simulation of the entire airfield may be required. At this stage, higher fidelity models such as AirTOp, TAAM, SIMMOD, CAST Aircraft, and RAMS come into play for more detailed modeling of the airfield. Table 13 outlines Study Purpose FAA’s Airport Capacity Benchmark Report Organization MITRE Environment Simulation studies in support of the development of airport capacity prediction benchmarks that used the predominant operating configurations of some of the busiest airports in the United States. This includes current airport layouts as well as any known future capital improvements. Model Used runwaySimulator Metrics Airport and runway capacity by configuration Resource and Data Requirements Current and future airport layouts Weather conditions Airport configuration and historic usage Airport facility reported arrival and departure rates (for validation) Fleet mix Applicability to Airport Planning/Design Airport runway system capacity planning Reference Kuzminski, 2013 Table 12. Runway-level capacity planning simulation case example.

Simulation Tool Application Guidelines 31 a higher fidelity simulation study of airport and runway capacity in which other factors such as taxiways, aprons, and gates are known to have had direct impacts on the overall airport and runway capacity. For higher fidelity airfield capacity and delay studies, the simulation effort mimics that of a master plan, but generally, capacity and delay studies focus more on throughput and delay metrics based on specific future demand rather than on the comparison of different layout alternatives. Figure 13. Simulation of John F. Kennedy International Airport using runwaySimulator. Source: FAA. Table 13. Runway and airport capacity simulation case example. Study Purpose New Airfield (Runway) and Capacity (London–Heathrow Airport), 2014 Organization Gatwick Airport Ltd./DFS Environment Simulations that assessed the operational benefits of a third runway at London–Heathrow International Airport (LHR). LHR is one of the world’s busiest and most efficient airports. This simulation study supported a larger capacity-demand study. Model Used TAAM/AirTOp Metrics Runway capacity Resource and Data Requirements Airport and runway layouts Flight schedules Arrival and departure procedures Runway dependencies and wake separations Applicability to Airport Planning/Design Runway capacity planning Reference DFS Deutsche Flugsicherung GmbH, Jan. 2015

32 Simulation Options for Airport Planning Terminal Passenger Flows A passenger’s first impression on their journey is the airport terminal. From the entrance to the boarding gate, the airport terminal is designed to ensure a seamless passenger experience from check-in through security checkpoints to the boarding areas. Airport terminals also offer commercial and entertainment facilities that passengers encounter and interact with along their travel paths. Among others, terminal design objectives generally focus on maximizing passen- ger throughput and minimizing queues at check-in and security screening points. Issues with terminal passenger flows can cause increased security threats, delays of connecting flights, and passengers missing their flights. An ever-present desire to provide efficient and enjoyable passenger flows and experiences within the terminal, combined with the need to maximize commercial and other revenue- generating facilities, creates a popular opportunity to apply simulation tools for both terminal design and operational planning purposes. The survey indicates that most airport planners use passenger flow simulation within the terminal structure primarily for the following types of studies: • Terminal passenger capacity planning. • Security checkpoint design and resource planning. • Check-in process capacity planning. About 50 percent of survey respondents indicated that they use simulation tools to directly influence terminal design decisions. However, it should be noted that there is no mandated use of passenger flow simulation tools for airport terminal planning. Simulation tools that focus on terminal passenger flow planning can provide significant value to the overall airport planning and design process. Such tools can assist in the definition and assessment of passenger paths both within and outside the terminal structure. They can also be used to discover passenger flow bottlenecks and to design adequate emergency evacu- ation routes. Passenger simulation tools are popular in industry because of their applicability to any number of other studies that evaluate passenger traffic. Relatively generic tools such as MassMotion, Arena, and Simio can not only be used to model airport terminal passenger traffic but also to model other areas such as train terminals and shopping malls. As the example in Figure 14 shows, the MassMotion terminal passenger simulation tool provides detailed visualizations of passenger movements that are supported by analytical capa- bilities that allow planners to analyze and fine-tune design decisions. Most generic passenger flow simulation tools can be tailored to specific airport environments, but the processes, queues, and constraints need to be well defined and understood. Table 14 illustrates the use of Arena to simulate check-in and security checkpoint queues using a com- bined flow model. Several planners also indicated that they use simulation tools for emergency evacuation and response scenarios. Table 15 presents a case example in which an agent-based model called BUMMPEE was used to simulate airport emergency evacuation procedures for dis- abled individuals. Some simulation tools such as AirTOp—which is primarily an airfield and airspace simula- tion tool—also provide modules that simulate terminal passenger flows. The benefit of using these higher fidelity tools for passenger flow analyses is that they may be readily linked to airfield models to provide a more holistic, integrated assessment of the entire interconnected airport system.

Simulation Tool Application Guidelines 33 Generally, passenger flow simulation tools use stochastic distributions of passenger transit and processing times to represent real-world processes. These distributions of historic passenger characteristics, behavior, and trends are based on data collected by the airport or through visual observation conducted purposely for the studies. Combined with information on capacitated queues and resources—such as check-in counters and security checkpoints—they represent the basic data requirements for terminal passenger simulations. As one might expect, the analysis metrics are geared toward processing times, delays, and resource usage. Some examples of passenger terminal flow simulation metrics are: • Passenger time in terminal. • Check-in and security wait delays. • Use of security checkpoints and staff. The results from these simulations can be used to assess terminal design decisions (i.e., pas- senger flow bottlenecks) as well as to optimize staffing and resource plans for objects such as security personnel and airline check-in counters. Figure 14. MassMotion terminal passenger simulation. Source: Oasys Software at http:// www.oasys-software.com/products/engineering/ massmotion.html. Study Purpose A Discrete Event Simulation to Model Passenger Flow in the Airport Terminal Organization Naples International Airport (Naples, Italy) Environment With a focus on check-in and security checkpoint processes, this study examined the use of simulation tools to improve the efficiency of check-in and security checkpoint procedures inside the airport terminal. Model Used Arena Metrics Hourly queue waiting time Number of users in the queue Resource and Data Requirements 1. Passenger arrival rate 2. Service time 3. Queue length Applicability to Airport Planning/Design Check-in and security planning Reference Guizzi et al., 2009 Table 14. Check-in process and security checkpoint case example.

34 Simulation Options for Airport Planning Terminal System Design and Planning In addition to passengers, terminal operations depend on the efficient operation of several other subsystems within the terminal structure. Passenger baggage systems are an integral terminal subsystem that connects passengers and their baggage with aircraft. Inefficiencies in this process can cause large-scale airport delays. There are several other processes that were mentioned frequently by airport planners as focus areas for simulation studies. Studies focused on interterminal train links and bus connections are also perfect candidates for the use of simulation tools. The majority of these types of studies use generic simulation tools that simply model processes using transit and process times, queues, and demand distributions with varying characteristics. Table 16 presents a case example of Riga International Airport’s baggage handling system using a simulation tool called ExtendSim. Study Purpose Modeling Emergency Evacuation of Individuals with Disabilities in a Densely Populated Airport Organization Transportation Research Board case example Environment Passenger terminal emergency evacuation study focused on the impacts of procedures and different passenger segments on terminal design Model Used Agent-based model (BUMMPEE) Metrics 1. Limitations of the pier airport design during emergency evacuations 2. Identification of the individuals most at risk or those with lower stamina 3. Potential bottleneck areas Resource and Data Requirements Terminal layouts Passenger demand information Population distributions of different passenger segments, including the nondisabled, motorized wheelchair users, visually impaired, etc. Applicability to Airport Planning/Design Evacuation planning Reference Manley et al., 2011. Table 15. Emergency evacuation and risk management case example. Study Purpose Riga International Airport Baggage Handling System Simulation Organization Transport and Telecommunication Institute Environment An increase in travel demand at Riga International Airport in Latvia requires an assessment of the current check-in and baggage system processes to ensure sufficient capacity for future demand growth. Model Used ExtendSim Metrics System utilization Queue length for check-ins Resource and Data Requirements Airport infrastructure (check-ins, conveyer length) Flight schedule (present and future) Aircraft and airline load factors Peak arrival times Check-in start and end time Applicability to Airport Planning/Design Check-in and baggage handling system planning and management Reference Savrasovs et al., 2009 Table 16. Baggage process simulation case example.

Simulation Tool Application Guidelines 35 Similar to passenger flow simulation tools, baggage system simulations depend heavily on focused input data. This includes daily passenger demand distributions, flight and gate sched- ules, the percentage of passengers that have checked versus carry-on baggage, the percentage of checked bags that undergo manual Transportation Security Administration checks, the percent- age of transiting versus origin-destination passengers, and so on. The analysis metrics from these terminal process simulation studies are customized depend- ing on the analysis scope and methodology. For baggage system simulations, airport planners may generally be interested in average and maximum bag time in the system, flights delayed due to late baggage arrivals, etc. Simulations of train and bus links may, however, focus more on passenger wait times in support of resource optimization and schedule planning studies. Ground-Access Studies Airport terminal curbsides represent critical interfaces between standing vehicles, moving vehicles, and pedestrians. They act as the capacity buffer between the road delivery system and the airport terminal building and represent the primary terminal access interface for passen- ger drop-off and pickup, including emergency access. The correct design and dimensioning of curbside areas is crucial for the efficient movement of passengers in and out of the terminal area. Although not as popular a focus for simulation studies, several airport planners noted that they frequently use various simulation tools for the planning, design, and operational impact analysis of curbside operations. Based on the survey responses, QATAR and Vissim are the most popular simulation tools for curbside operations. Some tools even have capabilities for roadway and intersection modeling, which can be used to assess the road interfaces between airport roadways and the highway infrastructure. A recent master plan update for Los Angeles International Airport used Vissim to simulate curbside and road operations to assess the traffic impacts of a new terminal concourse. Table 17 provides details for this example. Study Purpose Los Angeles International Airport master plan Organization Los Angeles World Airport Environment An assessment of potential traffic-related impacts associated with new facilities proposed as a part of the Midfield Satellite Concourse and the Central Terminal Processor Model Used Vissim (curbside, roadway) Metrics Level of service Resource and Data Requirements Traffic data for peak hour Traffic mix (heavy and nonheavy ratio, etc.) Future traffic conditions Aircraft/Airline load factors Airline passenger (PAX) schedules Vehicle counts and classifications Parking structure vehicle count Applicability to Airport Planning/Design On-airport surface transportation system Reference Los Angeles International Airport–Midfield Satellite Concourse, Draft EIR, available at: https://www.lawa.org/uploadedFiles/OurLAX/pdf/4_6_MSC_DEIR_On- Airport_Transportation.pdf. Table 17. Ground-access vehicle simulation case example.

36 Simulation Options for Airport Planning In many ways, the simulation tools used to model curbside operations are based on generic simulation principles that focus on queues and processing times. Data input requirements for curbside simulation tools generally include information on the roadway layout, vehicle traffic demand, vehicle traffic characteristics, and passenger and group characteristics, as well as airline and flight information for passengers to ensure that pickup and drop-off areas are used appropriately. As with other generic simulation tools, the analysis metrics will focus on the achieved level of service, delays, and throughput capacities. Airspace Procedure Design Airspace procedural changes are a necessary companion to airport studies that involve new runways. NextGen Performance Based Navigation (PBN) procedures focus on improving flight efficiency and reducing carbon footprints. Other factors such as airport and airspace capacity, safety, and environmental impacts also need to be considered when new airport arrival or departure procedures require evaluation. Simulation tools are frequently used in the design and evaluation phases of airspace proce- dure design studies. Terminal Area Route Generation and Traffic Simulation (TARGETS) and Instrument Approach Procedures Automation (IAPA) are the most commonly used procedure design tools and generally require specialized knowledge and expertise due to their focus on air traffic control operations and procedures. Although the proposed procedures are tested for fly- ability within these specialized software tools, the tools cannot assess flight efficiency, airspace impacts, conflicts, or economic benefits. This is particularly true in metropolitan environments where multiple large- and medium-size airports operate in close vicinity and procedures need to be internally optimized for flight profiles, but also deconflicted with other airport procedures at the same time. Several high-fidelity simulation tools are often used for this assessment, including AirTOp, TAAM, and SIMMOD. For example, FAA’s New York Airspace Redesign effort used TAAM to test and evaluate new RNAV/RNP procedures, route structures, and airspace sectorizations. This study explored operational impacts and supported subsequent environmental assess- ments. FAA and MITRE also used AirTOp as the simulation tool of choice for an airspace and procedure design feasibility analysis of a new proposed airport in the Chicago metropolitan area. More detail on this example is provided in Table 18. The benefit of using high-fidelity simulation tools for these assessments is that they can add a level of realism in terms of dynamic flight schedules—or demand—as well as simulate air- port and airfield operations, runway constraints, traffic flow management initiatives, and other en-route airspace restrictions. Some of the common metrics that are extracted from simulations for airspace procedure design studies include: • Airport and runway capacity. • Transition (SID/STAR) fix capacities. • Conflict points between procedures. • ATC sector throughputs or capacities. • Flight distances on procedures. • Climb and descent profiles on procedures. • Fuel burn and costs.

Simulation Tool Application Guidelines 37 Simulation tools can also feed noise and emission models that use flight tracks, traffic demand, and traffic mix information to visually depict changes in ground noise and emission impacts. This information can support subsequent EISs as well as public outreach efforts. Air Traffic Management Concept Evaluation A common question that airport planners frequently face is whether an airport is NextGen- capable. Technologies such as PBN, arrival and departure management, 4-D trajectory-based operations, information sharing, and enhanced ATC surveillance are some of the NextGen concepts that airports are routinely preparing to accommodate. Requirements for operational improvements are continuously requested by airlines and business aircraft operators to reduce delays and drive profits. These improvements can be focused on the airport surface, such as with advanced departure managers, or in the airspace as with PBN procedures, continuous descent and climb operations, and the like. For example, at San Francisco International Airport FAA evaluated and implemented closely spaced parallel operations using TAAM as their simulation tool of choice. Closely spaced parallel runways are spaced less than 2,500 feet apart and are authorized for 1.5-nautical mile depen- dent staggered approaches. FAA continued to use simulation tools to assess these benefits and eventually implemented closely spaced parallel operations in Boston, Cleveland, Memphis, Newark, Philadelphia, Salt Lake City, San Francisco, and Seattle. NextGen technology-focused simulations require input data that are fairly detailed and fre- quently more labor intensive to process. The primary reason for this is simply that simulation Study Purpose Initial Airspace and Procedures Feasibility Analysis for the Proposed South Suburban Airport (SSA) Organization FAA and MITRE Environment The project’s primary objective was to examine the existing Chicago metropolitan area air traffic and airspace structure to determine the feasibility and challenges of integrating a supplemental commercial airport (SSA) into the existing structure. Model Used AirTOp Metrics Throughput by airport Ground delay by airport Time in level flight by airport Flight time by airport Potential conflicts requiring ATC resolution Prearranged coordination climb operations involving new procedures Distance in level flight for proposed SSA departures Resource and Data Requirements Current SIDs, STARs, airspace, and runway operations at ORD and MDW Proposed SSA RNAV SIDs and STARs using TARGETS software Proposed airspace design changes Varying demand and schedule scenarios East and west flow scenarios Applicability to Airport Planning/Design Airspace procedure design and planning ATC impacts Reference Initial Airspace and Procedures Feasibility Analysis for the Proposed South Suburban Airport (SSA), available at: http://www.southsuburbanairport.com/MasterPlan/reports/MP-Report- Airspace.htm. Table 18. Airspace procedure design simulation case example.

38 Simulation Options for Airport Planning studies in support of NextGen technology evaluations usually require the use of multiple simula- tion tools and data input/output interfaces must be supported. This is particularly true because simulation tools are rarely purpose-built to be able to directly model future concepts and tech- nologies. For example, simulation studies that focus on the benefits of advanced arrival managers will likely require the use of other software tools to preprocess flight schedules and provide advanced arrival sequences that can then be integrated and simulated in other high-fidelity tools such as AirTOp, TAAM, or SIMMOD. Table 19 demonstrates the use of TAAM for a conceptual study on the benefits of Con tinuous Descent Operations (CDOs) at Hartsfield–Jackson Atlanta International Airport. Another popular tool for the analysis of systemwide impacts of future air traffic manage- ment concepts and technologies is NASA’s FACET simulation tool. FACET was designed to focus more on the National Airspace System (NAS) and macroscopic impacts of future technologies than on individual airports or airfields and facilities. So, it may be better suited to simulating impacts of airspace-related future NextGen and Single European Sky ATM Research (SESAR) concepts such as Arrival Manager/Departure Manager (AMAN/ DMAN) and 4-D trajectories. This is similarly true for DART, which is a newer simulation tool that can very quickly model aircraft across the entire NAS. DART uses weather data (convective and nonconvective) in addition to wind information for simulation and analysis purposes. Because simulations of future concepts are typically conceptual and conducted at a high level, the analysis metrics are generally geared toward assessments of airspace and ATC impacts, ATC and runway throughput capacities, and flight efficiency. Depending on the concepts and technologies being evaluated, it is not uncommon to simulate future operations using high-fidelity simulation tools with existing master planning or capacity and delay models to increase the realism of the overall assessment. Metrics and Analysis Most airport planners and designers—more than 85 percent based on the survey—use sim- ulation tools for strategic, long-term planning projects. These types of projects are generally driven by capital improvements in which simulation results are used to justify design and con- struction decisions. Study Purpose Assess Benefits of CDOs at Atlanta International Airport Organization Embry-Riddle Aeronautical University Environment A flight efficiency comparison of existing arrival procedures (STARs) at Hartsfield–Jackson Atlanta International Airport and proposed RNAV/RNP Continuous Descent Operations procedures with two-dimensional (2-D) track freedom. Model Used TAAM Metrics Flight time, fuel cost, ATC conflicts Resource and Data Requirements Traffic demand schedule, fleet mix, current and proposed SID and STAR configurations, route structures and use of arrival and departure fix Applicability to Airport Planning/Design Future ATC procedure concept evaluation Reference Wilson and Hafner, 2005. Table 19. Future concept case example.

Simulation Tool Application Guidelines 39 However, more than 50 percent of the survey respondents also noted that they frequently use simulation tools for more tactical operations planning tasks. The types of projects noted include: • Near-term improvements that assume the use of existing procedures and technology. • Baggage systems and work zone impacts. • Construction planning and TFM initiatives. • Construction phasing and specific capacity. • Operational planning. • On-call planning work that requires simulation tools to complete daily tasks. These types of studies may require different analysis methods and usually have shorter turn- around times because they impact near-term operations. Metrics obtained from these simulation tools can generally be classified as: • Summary statistics. • Dynamic demand-driven graphs and tables. • Visualizations of simulated traffic. As Figure 15 shows, the vast majority of airport planners that responded to the survey use detailed simulation metrics and derived Excel spreadsheet analysis tools in their analyses and Delay Times Comparison Scatterplots; Influence Diagrams; Regressions; Factor Analysis Cumulative Distributions (CDFs) Histograms/Bar Charts Percentiles of Confidence Intervals (i.e., 95%) Means/Averages (hourly, daily, by aircraft/passenger, etc.) Figure 15. Survey results—simulation metrics and statistics.

40 Simulation Options for Airport Planning report presentations. Frequently, the need for more detailed metrics may require custom soft- ware tools to extract and analyze simulation data. Metrics are then summarized using basic means and averages (e.g., daily, hourly, or by aircraft and passenger), confidence intervals, or standard histograms. Simulation tool outputs are also frequently used to support other applications and tools. These ancillary models range from more sophisticated visualization and analysis tools— including statistical and financial—to models that support more detailed analyses of secondary factors such as noise, emissions, gating plans, or vehicle and parking ingress and egress. Figure 16 lists all of the secondary tools and models noted by survey respondents. An important aspect of simulation analysis that should not be overlooked, however, is that of study and result validity and reliability. The majority of airport planners or organizations gener- ally find simulation results to be reliable and truthful. However, several noted that the reliability of simulation study results is directly dependent on factors such as • Input data availability and quality. • The supporting simulation and study methodology. • The analysts. • Stakeholder participation and agreement. Figure 16. Secondary models using simulation output data.

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Global business and tourism depend heavily on the efficient operation of airports and movement of passengers, baggage, and cargo across many areas. With increasing demand and connectivity requirements for airports comes the need for more sophisticated simulation and modeling tools to validate design assumptions.

Furthermore, airport design and planning decisions have significant impacts on policy and major capital improvement decisions, which can be supported by simulation and modeling tools at many levels.

ACRP Synthesis 98: Simulation Options for Airport Planning is the result of the collection and analysis of information on current industry practices and on applications of simulation tools for airport planning and design. Credible simulation projects can help airport administrators, designers, engineers, and planners estimate the impact of planned changes on passenger traffic, aircraft traffic, roadway traffic, baggage movements, and other subsystems such as bus and train links and aircraft ground support operations.

The toolsets and processes used to analyze and simulate airport operations have changed significantly since the 1980s, when analysis techniques were limited to general purpose queuing and network analysis concepts or purpose-built simulation tools. These tools have become much more sophisticated and accurate in emulating real-world aircraft, passenger, and vehicle dynamics.

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