NASA/TM-2015-218699 

System-Oriented Runway Management 

Concept of Operations 

Gary W. Lohr 

Langley Research Center, Hampton, Virginia 

Stephen Atkins 

Mosaic ATM Inc., Leesburg, Virginia

March 2015
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NASA/TM-2015-218699 

System-Oriented Runway Management 

Concept of Operations 

Gary W. Lohr 

Langley Research Center, Hampton, Virginia 

Stephen Atkins 

Mosaic ATM Inc., Leesburg, Virginia

March 2015
Available from: 

NASA STI Program / Mail Stop 148 

NASA Langley Research Center 

Hampton, VA 23681-2199 

Fax: 757-864-6500 

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Space Administration. 
SORM Concept of Operations

i

Table of Contents

Introduction......................................................................................................................... 1

Document Organization ................................................................................................... 2

Background......................................................................................................................... 3

National Aeronautics and Space Administration (NASA) Airspace Systems Program 

Research........................................................................................................................... 3

Current Air Traffic Operations Related to Runway Management ................................... 5

Tactical Airport Configuration Selection.................................................................. 5

Coordinated Runway Scheduling ............................................................................. 6

Strategic Airport Capacity Planning ......................................................................... 7

System-Oriented Runway Management Concept Overview ........................................... 7

Strategic Runway Configuration Management......................................................... 8

Tactical Runway Configuration Management.......................................................... 8

Combined Arrival/Departure Runway Scheduling .................................................. 8

SORM in the Operational Environment ................................................................... 9

Related Research ............................................................................................................ 10

Super Density Operations Research Area............................................................... 11

Safe and Efficient Surface Operations Research Area ........................................... 12

Dynamic Airspace Configuration Research Area................................................... 13

Traffic Flow Management (TFM) .......................................................................... 14

Other Related Research Activities.......................................................................... 14

Tactical Runway Configuration Management (TRCM)................................................... 15

Introduction to TRCM.................................................................................................... 15

Airport vs. Runway Configuration ......................................................................... 16

Airport vs. Runway Capacity.................................................................................. 18

TRCM Algorithm........................................................................................................... 20

TRCM Adaptation.......................................................................................................... 21

Airport Configuration Definition............................................................................ 22

Factors that Affect Airport Configuration .............................................................. 23

TRCM System Design ................................................................................................... 26

TRCM Problem Description .......................................................................................... 28

Evaluation....................................................................................................................... 30

Runway Usage Example ......................................................................................... 30

Runway Assignment Example................................................................................ 31

Runway Configuration Examples........................................................................... 33

TRCM Benefit Mechanisms .......................................................................................... 34

Summary of the TRCM Concept and Algorithm Development .................................... 35

Strategic Runway Configuration Management (SRCM).................................................. 38

SRCM Overview............................................................................................................ 38

SRCM Algorithm........................................................................................................... 39
SORM Concept of Operations

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Combined Arrival/Departure Runway Scheduling (CADRS).......................................... 40

CADRS Overview.......................................................................................................... 40

CADRS Algorithm......................................................................................................... 41

Factors that Affect Runway Assignment and Sequencing/Scheduling................... 42

Information Requirements................................................................................................ 47

SORM Stakeholders....................................................................................................... 47

Strategic Runway Configuration Management.............................................................. 53

Information Required by SRCM............................................................................. 53

Information Provided by SRCM............................................................................. 54

Entities that Interact with SRCM............................................................................ 54

Tactical Runway Configuration Management ............................................................... 55

Information Required by TRCM ............................................................................ 55

Information Provided by TRCM............................................................................. 55

Entities that Interact with TRCM............................................................................ 55

Combined Arrival Departure Runway Scheduling ....................................................... 56

Information Required by CADRS .......................................................................... 56

Information Provided by CADRS........................................................................... 56

Entities that Interact with CADRS.......................................................................... 57

SORM Research and Development Status ....................................................................... 58

Summary........................................................................................................................... 60

Bibliography ..................................................................................................................... 62

Works Cited.................................................................................................................... 62

Guide to Further Reading............................................................................................... 63

Examples of airport Geometries.......................................................................... 65

Descriptions of Decision Making process for Runway Configuration Selection at 

Two Select Airports............................................................................................. 67

B.1. Dallas-Fort Worth International Airport Example ......................................................... 67

B.2. Memphis International Airport Example ....................................................................... 68

An Airport Runway Management User Interface and Decision Support 

Toolset................................................................................................................... 71
SORM Concept of Operations

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List of Figures

Figure 1. KATL baseline departure runway assignment procedures........................................... 18

Figure 2. Planned John F. Kennedy International Airport arrival and departure capacities for 

different instances of runway configuration 31R/31L in visual meteorological 

conditions................................................................................................................... 19

Figure 3. Tactical Runway Configuration Management in MSE. ................................................ 59

Figure A-1. Los Angeles International Airport............................................................................ 65

Figure A-2. John F. Kennedy International Airport. ................................................................... 65

Figure A-3. San Francisco International Airport. ........................................................................ 65

Figure A-4. Ronald Reagan Washington International Airport................................................... 65

Figure A-5. General Edward Lawrence International Airport..................................................... 65

Figure A-6. San Diego International Airport............................................................................... 66

Figure A-7. Philadelphia International Airport............................................................................ 66

Figure A-8. Dallas-Fort Worth International Airport. ................................................................. 66

Figure B-1. Memphis International Airport................................................................................. 69

Figure C-1. SAOD Process.......................................................................................................... 71

Figure C-2. Preliminary GUI design............................................................................................ 72

List of Tables

Table 1. Initial Elements of Airport Configuration ..................................................................... 22

Table 2. Future Elements of Airport Configuration..................................................................... 23

Table 3. Weather Factors that Affect Airport Configuration....................................................... 23

Table 4. Non-weather Factors that Affect Airport Configuration ............................................... 25

Table 5. Approximate Taxi Distances from Ramps to Departure Runways................................ 32

Table 6. Tactical Runway Configuration Management Results at Orlando International Airport

................................................................................................................................... 33

Table 7. Tactical Runway Configuration Management Benefit Mechanisms............................. 34

Table 8. Factors that Affect Runway Usage ................................................................................ 43

Table 9. System-Oriented Runway Management Stakeholders .................................................. 47

Table 10. Strategic Runway Configuration Management Stakeholders and Information 

Exchanged.................................................................................................................. 54

Table 11. Tactical Runway Configuration Management Stakeholders and Information 

Exchanged.................................................................................................................. 55

Table 12. Combined Arrival Departure Runway Scheduling Stakeholders and Information 

Exchanged.................................................................................................................. 57
SORM Concept of Operations

iv

Abbreviations and Acronyms

4D CARMA...............Four-Dimensional Cooperative Arrival Management 

AAR...........................airport acceptance rate

ARMD........................Aeronautics Research Mission Directorate

AOC...........................Airline Operations Center

ARTCC......................air route traffic control center

ARTS .........................Automated Radar Terminal System

ASPM.........................Aviation System Performance Metrics

ATC............................air traffic control

ATCSCC....................Air Traffic Control System Command Center

ATCT.........................airport traffic control tower 

ATIS...........................Automatic Terminal Information System

ATL............................Hartsfield-Jackson Atlanta International Airport

ATM...........................air traffic management

CADEO......................Controller Assistance for Departure Optimization

CADM........................Coordinated Arrival Departure Manager

CADRS ......................Combined Arrival/Departure Runway Scheduling

CAIRO .......................Complete Airport Optimizer

CIC.............................controller in charge

DLR............................Deutsches Zentrum für Luft- und Raumfahrt; German Aerospace Center

DST............................decision support tool

EDCT.........................expected departure clearance time

ERAM........................en route automation modernization

ESIS ...........................Enhanced Status Information System

ETMS.........................Enhanced Traffic Management System

FAA............................Federal Aviation Administration

FCFS ..........................first-come, first-served

GDTA ........................Goal-directed Task Analysis

GI ...............................general information

GUI ............................graphical user interface

IAP .............................instrument approach procedure

ILS..............................Instrument Landing System

ITWS..........................Integrated Terminal Weather Service

JPDO..........................Joint Planning and Development Office

KBOS.........................Boston Logan International Airport

KDFW........................Dallas-Fort Worth International Airport

KJFK..........................John F. Kennedy International Airport

KLAX ........................Los Angeles International Airport

KLGA ........................LaGuardia Airport

KMCO........................Orlando International Airport
SORM Concept of Operations

v

KMEM.......................Memphis International Airport

LAHSO ......................Land and Hold Short

McTMA .....................Multi-center Traffic Management Advisor

MIT ............................miles-in-trail

MSE ...........................Metroplex Simulation Environment

NAS............................National Airspace System

NASA.........................National Aeronautics and Space Administration

NRA...........................NASA Research Announcement

NTML ........................National Traffic Management Log

NWS...........................National Weather Service

RCM...........................Runway Configuration Management

RNP............................required navigation performance

SAIE...........................Systems Analysis, Integration & Evaluation

SAOD.........................Situation Awareness-oriented Design

SDO............................Super Density Operations

SESO..........................Safe and Efficient Surface Operations

SOP ............................Standard Operating Procedure

SORM ........................System-Oriented Runway Management

SRCM ........................Strategic Runway Configuration Management

STARS.......................Standard Terminal Automation Replacement System

TFDM ........................Tower Flight Data Manager

TFM ...........................traffic flow management

TFMS .........................Traffic Flow Management System

TMA...........................Traffic Management Advisor

TMC...........................traffic management coordinator

TMI............................traffic management initiative

TMU...........................Traffic Management Unit

TRACON...................Terminal Radar Approach Control

TRCM ........................Tactical Runway Configuration Management
SORM Concept of Operations

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Introduction

This document describes a concept for runway management that maximizes the overall 

efficiency of arrival and departure operations at an airport or group of airports. Specifically, by 

planning airport runway configurations/usage, it focuses on the efficiency with which arrival 

flights reach their parking gates from their arrival fixes and departure flights exit the terminal 

airspace from their parking gates. In the future, the concept could be expanded to include the 

management of other limited airport resources. While most easily described in the context of a 

single airport, the concept applies equally well to a group of airports that comprise a metroplex

(i.e., airports in close proximity that share resources such that operations at the airports are at 

least partially dependent) by including the coordination of runway usage decisions between the 

airports. In fact, the potential benefit of the concept is expected to be larger in future metroplex 

environments due to the increasing need to coordinate the operations at proximate airports to 

more efficiently share limited airspace resources. This concept, called System-Oriented Runway 

Management (SORM), is further broken down into a set of airport traffic management functions 

that share the principle that operational performance must be measured over the complete surface 

and airborne trajectories of the airport’s arrivals and departures. The “system-oriented” term 

derives from the belief that the traffic management objective must consider the efficiency of 

operations over a wide range of aircraft movements and National Airspace System (NAS) 

dynamics. The SORM concept is comprised of three primary elements: strategic airport capacity 

planning, airport configuration management, and combined arrival/departure runway planning. 

Some aspects of the SORM concept, such as using airport configuration management1as a 

mechanism for improving aircraft efficiency, are novel. Other elements (e.g., runway scheduling,

which is a part of combined arrival/departure runway scheduling) have been well studied, but are 

included in the concept for completeness and to allow the concept to define the necessary 

relationship among the elements. 

The goal of this document is to describe the overall SORM concept and how it would apply both 

within the NAS and potential future Next Generation Air Traffic System (NextGen)

environments, including research conducted to date. Note that the concept is based on the belief 

that runways are the primary constraint and the decision point for controlling efficiency, but the 

efficiency of runway management must be measured over a wide range of space and time. 

Implementation of the SORM concept is envisioned through a collection of complementary, 

necessary capabilities collectively focused on ensuring efficient arrival and departure traffic 

management, where that efficiency is measured not only in terms of runway efficiency but in 

terms of the overall trajectories between parking gates and transition fixes. For the more original 

elements of the concept—airport configuration management—this document proposes specific 

air traffic management (ATM) decision-support automation for realizing the concept.

 

1

In the development of the SORM concept, it is recognized that effective runway management requires inclusion of 

factors affecting operations on, and in the immediate vicinity of, the airport. In this regard runway management is a 

part of airport configuration management.
SORM Concept of Operations

2

Document Organization

The next section provides background and motivation for SORM research, describes current 

operations that will be affected by SORM, and introduces the elements of the SORM concept. 

Each of the SORM components is discussed in sections 3.0–1.0; section 1.0 presents information 

requirements for stakeholders and each of the SORM elements; section 1.0 summarizes the 

current state of the research and is followed by an overall Summary in section 1.0. Note that as 

part of this document, historical elements of the concept creation are included for completeness.
SORM Concept of Operations

3

Background

The air traffic system is becoming increasingly complex. New technologies and operational 

procedures are being considered and deployed to address increase system capacity, reduce 

delays, improve aircraft efficiency, reduce fuel burn for both operating cost and environmental 

benefits, increase reliability in poor weather conditions, and improve system safety.

Enhanced surveillance capabilities, such as the use of automatic dependent surveillance and 

airport surface surveillance, and the proliferation of area navigation approaches and departures 

signal the need for complementary capabilities to optimize air traffic operations. Many new 

concepts leveraging new technologies and focusing on increasing safety and efficiency in the 

NAS are being investigated. Some new concepts strive to increase capacity for operations in 

enroute airspace, while others focus on terminal airspace operations. Considerable research has 

been performed to quantify wake hazards in order to determine if reductions to current wake 

separations are possible. For example, analysis of wake hazards has resulted in a rule change 

that reduces the required diagonal separation for dependent approaches (ref. 9.1) that may be 

expanded to additional situations in the future. More recently, “Re-categorization” or “Re-cat” 

(ref. 2) by aircraft types promises to significantly increase capacity. Changes in required 

separation standards enable higher traffic rates on runways, stressing the airspace routes to those 

runways and the taxiway system carrying aircraft away from those runways. 

National Aeronautics and Space Administration (NASA) Airspace 

Systems Program Research

As studies on concepts focused on efficiency of operations in various air traffic domains 

continue, the efficient use of runways becomes paramount. Furthermore, runway usage must be 

efficient with respect to both local airport issues and systemic, NAS-wide goals. An often 

overlooked “control knob” that significantly affects how efficiently runways are used is the 

selection of the runway configuration. The SORM concept is envisioned to directly address 

these needs. 

The National Aeronautics and Space Administration’s (NASA) Aeronautics Research Mission 

Directorate (ARMD) is pursuing focused research to help the nation achieve revolutionary 

advancements in air traffic management. The Joint Planning and Development Office (JPDO)2

NextGen Concept of Operations (ref. 3) provided direction for ARMD’s pursuit of research 

toward improving the NAS, stating that “during the next two decades, demand will increase.” 

While the magnitude of potential traffic increases has been debated, increased demand, fuel 

costs, and environmental awareness will all necessitate enhanced air traffic management system 

capabilities. To address necessary changes in the NAS, NASA developed a research plan under 

the Airspace Systems Program (ASP). Until recently, the ASP was comprised of two projects: 

the NextGen Concept & Technology Development Project and the NextGen Systems Analysis, 

Integration & Evaluation Project (SAIE). As most of the SORM work was conducted under this

organizational structure, it will be referenced in this document. Concepts and Technology 

 

2 At the time of the creation of the runway management research effort and during most of the life of the work, the 

JPDO was the guiding influence for NextGen activities. It has since been replaced, and is included here for historic 

reference.
SORM Concept of Operations

4

Development was composed of research areas that addressed the following: Dynamic Airspace 

Configuration, Traffic Flow Management, Separation Assurance, Super Density Operations, and 

Safe and Efficient Surface Operations. System-Oriented Runway Management research is part 

of the Super Density Operations research area. The SAIE Project was organized into four 

research areas: Exploratory Analysis, Portfolio Analysis, Interoperability Research, and 

Integration, Test, and Evaluation. 

The most current version of the original plan (ref. 4) cites the impact of effective runway 

management:

One of the biggest limiting factors in expanding air traffic capacity lies in airport 

operations, where a multitude of factors can cause flight delays and other incidents, 

the effects of which can cascade throughout the NAS. Airport capacity and 

efficiency is constrained at the individual airport level by surface operations 

(taxiways, ramps), runways (individually or interacting), and at the metroplex level 

due to interactions in the flow between nearby airports. Interacting flows between 

nearby metroplex airports are intricately linked to runway configuration and 

scheduling at the individual airports and must be treated as a system if system 

capacities and efficiencies are to be obtained.

Architects of the ASP determined that, among the capabilities being developed to support NextGen, a 

complimentary runway management capability was needed. The original focus was on runway 

balancing3. It quickly became apparent that this term was limiting in the context of the capability 

required. The research area was expanded to include a systemic approach to runway management 

and the inclusion of runway configuration selection. The two milestones from the original research 

plan were completed at the beginning of this research effort: 

 AP.1.C.01 Characterize current runway balance decision-making processes.

 AP.3.C.01 Catalog and assess alternatives for runway balancing and potential 

benefits.

The first milestone focused on a characterization of current practices for “runway balancing.” 

Results from the work on this milestone determined that the process of runway assignment was 

fairly rudimentary and that there was minimal coordination between arrival and departure flows 

at the airport level (ref. 5). Work addressing the second milestone essentially concluded that 

although alternatives for runway balancing could be defined, specific alternatives were not the 

solution. Rather, a set of capabilities were required with different weightings appropriate for 

different situations. This set of required capabilities evolved into the SORM concept. In 2014, 

the final milestone was completed with the development of an algorithm to address TRCM in a 

metroplex environment:

 AP.2.C.11 Extend Runway Configuration Management (RCM) and 

arrival/departure balancing algorithms to multiple airports with 

multiple runways.

 

3 The initial term for the area of work which ultimately became SORM was “runway balancing.” The area of work 

was expanded to reflect a systemic approach to runway management and the scope of the decisions that are required 

to efficiently utilize airport and terminal-area airspace resources.
SORM Concept of Operations

5

Planning the airport configuration has the potential to deliver substantial benefits at some 

airports within current operations and considerably greater benefits in the future as other 

technologies and procedural changes increase the airport configuration flexibility. However, 

NASA’s current airport traffic management research assumes the runway configuration is known 

and constant to focus on tactical control of individual flights through runway sequencing, taxi 

routing, and block-out metering of departures. Research under the SORM concept broadens and 

complements NASA’s portfolio of other airport traffic management research. More recent work 

under the SORM effort has been focused on a set of algorithmic capabilities to fulfill the SORM 

objectives. These algorithms were to be developed over a three-year period (2009–2012),

addressing increasing levels of operational complexity. The first two years addressed a single 

airport with single/multiple runways, and in the third year, multiple airports with multiple 

runways (metroplex). 

In May 2009, the SORM research team expanded significantly when NASA awarded a threeyear contract under a NASA Research Announcement (NRA) to Mosaic ATM, Inc. to support 

the continued development of SORM. Exploration of other aspects of the runway management 

problem has been conducted under contractual efforts and the Small Business Innovation 

Research Program.

The following three subsections (2.2–2.4) summarize the early work conducted in this area: a 

description of current practices in runway management operations, an overview of the SORM 

concept, and other related research.

Current Air Traffic Operations Related to Runway Management

The SORM concept, as envisioned, relates to the following airport traffic management functions: 

tactical airport configuration selection, strategic airport capacity planning, and coordinated 

runway scheduling. Current practices in each of these functional areas are described in the 

following sections.

Tactical Airport Configuration Selection

At most airports, the airport traffic control tower (ATCT) supervisor or controller-in-charge 

(CIC) has primary responsibility for selecting which runway configuration should be used and 

any other procedures for which options are available. The degree to which efficiency can be 

achieved is a function of many factors including taxiway structure, area availability to absorb 

traffic overload, and availability of low weather instrument approaches.

As this decision becomes more complex due to traffic flow management issues, traffic 

management coordinators (TMCs) are becoming more involved. For example, the New York 

Terminal Radar Approach Control (TRACON) (N90) Traffic Management Unit (TMU) has 

authority to dictate the runway configurations to be used at New York metroplex airports, due to 

the need to coordinate the configurations at the airports. References 6 and 7 provide additional 

information on current procedures for selecting the runway configuration. Some of the 

considerations for selecting active runways are as follows:

 Surface wind velocity

 Meteorological conditions
SORM Concept of Operations

6

 Traffic demand

 Shear/microburst alerts/reports

 Adjacent airport traffic flows

 Severe weather activity

 instrument flight rules departure restrictions

 Environmental factors

 Intersecting arrival/departure runways

 Distance between arrival runways

 Dual purpose runways (shared arrivals and departures)

 land and hold short (LAHSO) utilization

 Availability of high speed taxiways,

 Potential for use of reduced (2.5 nm) separation rule for arrivals

 Airspace limitations/constraints

 Procedural limitations (missed approach protection, noise abatement, etc.)

 Taxiway layouts

 Terminal flow of traffic

The primary considerations for runway selection are wind direction and speed; thresholds for 

these values have been established in the interest of safe operations. The FAA Order 8400.9 (ref. 

6) defines maximum tailwind and crosswind limits for runway operations, allowing for sitespecific exceptions; also in this document is the establishment of runway-use programs, which 

address the application of noise restrictions. These criteria represent “hard” constraints in the 

runway selection process. At major airports, pre-defined runway configurations are defined and 

set forth in facility directives. Runway configurations serve as a basis for a flow of traffic on the 

airport surface as well as for arrival and departure traffic. Configurations are selected, in large 

part to accommodate a desired ratio of arrivals and departures. As configurations are selected, 

the TRACON providing approach control services for the subject airport determines the type of 

approach in use for each active runway. In general, visual approaches are used when possible, as 

they usually provide the greatest capacity. Examples of how some of the factors involved in the 

decision-making process are used are described in Appendix B for two different airports.

Coordinated Runway Scheduling

In current operations, runway assignments are most frequently based on a logical strategy that 

follows a basic procedure. Departure aircraft are assigned to the runway (from the set of active 

runways useable by that aircraft type) that is most closely aligned with their initial direction of 

flight (i.e., toward their departure fix). If a set of parallel runways are used for departures, some 

aircraft will need to make a turn of about 180 degrees to reach a departure fix in the opposite 

direction. Sequencing strategies are used to ensure divergent headings between successive 

departures, which take advantage of rules permitting reduced separations when courses 
SORM Concept of Operations

7

immediately diverge and requisite weather criteria is met. Significant changes in sequencing are 

precluded by respecting the first-come, first-served principal and by controller workload, unless 

traffic flow management restrictions demand otherwise. Other factors that influence departure 

runway assignment are runway length requirements for larger aircraft, noise restrictions, cross 

winds, and traffic volume. 

Arrivals are generally assigned runways closest to their arrival fixes (usually at the terminal 

boundary), although parking position is considered, when traffic conditions permit, at some 

airports in order to reduce taxi distance. Load balancing for both the routes through the terminal 

area as well as the runways result in exceptions to this rule. Also in today’s environment, 

attempts are sometimes made to sequence aircraft to reduce the impact of the wake vortex 

separation requirement. Changing the ordering of aircraft for better wake turbulence spacing can 

result in an overall reduction of the spacing required across an arrival stream and for departures. 

With the limited TRACON airspace and high workload for approach controllers, this is often not 

practical when demand is high, although it could be beneficial in reducing arrival delays.

Strategic Airport Capacity Planning

Operations between arrivals and departures are generally not coordinated in today’s 

environment. In the case of dedicated arrival and departure runways, this is not a tactical 

problem. As the need for higher levels of efficiency for airport operations increases, greater 

planning and execution of strategies will be required. An example is consideration of airport 

surface congestion; minimal spacing between arrivals and departures may not permit the number 

of runway crossings required to facilitate a reasonably efficient surface traffic flow. Hence, 

sacrifices may be required in terms of capacity and consideration must be given to whether these 

sacrifices will benefit the system as a whole. A further complicating factor is occasional 

capacity imbalances at the airport, where trade-offs may be required between arrival and 

departure loading of the runways. This propagates in the larger context of a metroplex where 

dependencies extend into the airspace where paths conflict flight and there is competition for 

shared departure fixes.

Traffic flow management decisions must often be made many hours in advance. For example, if 

severe weather will reduce the capacity of an airport and result in many flights being delayed, the 

most efficient place for those flights to incur the necessary delays is on the ground prior to 

departure, with their engines not yet running. For delayed flights that originate at locations that 

are several hours flying time from the weather-impacted airport, the traffic flow management

(TFM) decision about how to delay them would have to be made before the time they would be 

departing, which would be several hours in advance of the severe weather impacting the airport. 

At this long time-horizon, specific decisions about the airport configuration that will be used 

during the severe weather have not been made and, therefore, are not available to the TFM

decision process. However, that TFM decision process must be informed by some estimate of 

what will happen at the airport.

System-Oriented Runway Management Concept Overview

The initial SORM concept was comprised of two elements: Runway Configuration Management 

(RCM) and Combined Arrival/Departure Runway Scheduling (CADRS). Runway Configuration 

Management is considered to be the process of designating the active runways, monitoring the 
SORM Concept of Operations

8

active runway configuration for suitability given existing factors, and predicting future 

configuration changes. Combined Arrival/Departure Runway Scheduling is the process by 

which arrivals and departures are assigned runways based on local airport and NAS goals 

through the effective distribution of arrival and departure traffic across active runways in 

conjunction with effective scheduling of traffic on those runways. 

Initial SORM research on current practices necessitated refining the set of capabilities that 

should be included within the SORM concept and how those capabilities should be organized 

into components. Based on observed current practices, the refined SORM concepts comprise 

three functions: strategic airport capacity planning, airport configuration management, and 

combined arrival/departure runway planning. Strategic airport capacity planning was added to 

the SORM concept to recognize the need to connect airport planning with traffic flow 

management decisions over a longer time horizon than the original SORM concept 

encompassed. RCM was split into two components based on the elements of the SORM concept 

that existed in present-day operations and elements that would require more significant 

operational changes. A brief description of the three components currently being developed 

within SORM: TRCM, SRCM, and CADRS, follows with more detailed descriptions in sections

3.0–1.0.

Strategic Runway Configuration Management

Strategic Runway Configuration Management forecasts the airport configuration over a longer 

time horizon for the purpose of providing airport capacity forecasts for use in traffic flow 

management—planning traffic management initiatives (TMIs) several hours in advance. This 

capability is also seen as beneficial to NAS system users in planning resources. A strategic 

element of SORM could make an early prediction for the airport arrival and departure capacities. 

While the output of this function would be a coordinated capacity forecast, underlying this 

forecast would be determination of the most likely airport configurations and times at which the 

configuration would change.

Tactical Runway Configuration Management

Tactical Runway Configuration Management plans the airport configuration over a timeframe 

appropriate for air traffic personnel in the ATCT and TRACON to make runway configuration 

and operating procedure decisions used to control arrival and departure traffic. Despite the 

name, which is retained for historical reasons, TRCM goes beyond selecting runway 

configurations and also selects aggregate policies for the active runways’ usage. Note that the 

FAA uses the term Airport Configuration Management to refer to the TRCM capability.

Combined Arrival/Departure Runway Scheduling

Combined Arrival/Departure Runway Scheduling is more tactical in nature than TRCM; it plans

how individual flights should use the available runways and is subject to (or in exception to) the 

aggregate policies selected by TRCM. The CADRS concept considers runway assignments and 

aircraft sequencing, airport surface, and TFM factors. The concept does not imply any particular 

approach to achieving runway operations that are efficient from the perspective of the complete 

trajectories between parking gates and transition fixes. The envisioned CADRS capability is 
SORM Concept of Operations

9

intended to efficiently plan the use of the selected runway configurations. This includes 

consideration of arrival and departure traffic as well as aircraft taxiing across runways.

SORM in the Operational Environment 

This organization of functions differs from the initial SORM concept in two significant ways, the 

most obvious being the addition of the strategic airport capacity forecasting function. In 

addition, TRCM subsumes the original RCM as well as elements of the original CADRS 

definition. Under the new concept, CADRS is focused on tactical planning of flight-specific 

runway usage decisions such as sequencing or scheduling at the runway and runway assignments 

that are exceptions to the TRCM-defined policies. This reorganization allows the runway 

configuration and runway usage policy decisions that must be made together to be within the 

same SORM component. It also separates SORM elements that could readily be deployed 

within the NAS from those that will require more substantial operational changes.

The SORM concept assumes that automation will be used to provide advisories to air traffic 

controllers, supervisors, and traffic managers to achieve the SORM vision of efficient runway 

utilization. Further investigation of the role of the human and automation in the SORM concept 

is essential. In addition to considering the traffic demand and other factors such as controller 

staffing and status of navigational aids that affect available runways and procedures, SORM 

must consider airport surface weather conditions as well as terminal airspace weather such as 

winds and the presence of convective cells. Current limitations of airport surface weather 

forecasting capabilities prevent the fully automated planning of runway configurations. Future 

weather forecast products are expected to provide finer resolution information of when surface 

winds will change direction, for example, eliminating the need for controllers4to interact with 

SORM to provide sufficient weather forecast information.

The cornerstone of the SORM concept is the consideration of the efficiency of all phases of 

arrival and departure operations, rather than attempting to optimize only the throughput or delays 

at the runways. For example, SORM considers how different uses of the runways might cause or 

avoid taxi congestion or excessive demand for a particular departure fix, which may affect 

aircraft delays and fuel burn more than the variations that would occur in runway delays if nonrunway resources were not constrained. System-Oriented Runway Management avoids 

situations in which the runway configuration provides a higher departure capacity at the runways 

when the departure fixes are closed or the departure aircraft cannot reach the runways due to 

surface gridlock. While the concept encompasses control mechanisms used by many other 

concepts, such as runway scheduling, SORM is unique in its inclusion of runway configuration 

and other aspects of airport configuration as key control mechanisms for maximizing overall 

operational efficiency. The concept provides for the incorporation of inputs from all service 

providers that are responsible for the administration of air traffic operations, in addition to the 

system users (airlines and general aviation, among others) and airport operators (those who 

essentially “own” the airport).

 

4 The use of the term “controllers” is meant in a global sense; it includes those performing the tactical control of 

aircraft (including supervisors) as well as traffic flow management personnel.
SORM Concept of Operations

10

System-Oriented Runway Management uses runway configuration and other runway usage 

decisions to improve the efficiency of arrival and departure operations at an airport while 

considering traffic flow management objectives and restrictions. The longer term vision of 

SORM is to provide for these capabilities in a metroplex environment, which poses additional

challenges due to the need to coordinate runway usage plans between airports. The selection of 

runway configurations across airports within a given metroplex area requires consideration of the 

role of each airport in the grander context of NAS efficiency.

The future holds greater complexities based on the promise of future NAS enhancements, e.g., 

weather products with more accuracy and longer planning horizons, greater accuracy in 

delivering aircraft to the runway based on required times of arrival, and likely further changes in 

wake vortex separation standards, among others. The core objective of SORM is to provide a set 

of capabilities that assimilate information from relevant sources and provide algorithmic 

solutions for runway management and assignment. It should be noted that SORM is intended to 

provide recommendations; the human always makes the final decision. 

A final note regarding the runway management process that the SORM concept addresses.

Although the approach taken with the SORM concept could improve operations at most airports, 

it is not a simple matter of deploying the tools to any airport without consideration for the 

operating environment. System-Oriented Runway Management requires a detailed adaptation 

that is specific to each airport’s operating environment, in order to achieve its objectives of 

optimizing airport operations while considering the different and disparate factors that can affect 

these operations. There are, in fact, common denominators that define operations across airports; 

however their uniqueness requires consideration. The sampling of airport configurations shown 

in Appendix A underscores the significant differences that exist between airports and the need to 

reflect those differences in crafting effective runway management solutions. Note that those 

depictions found in the referenced appendix reflect only the geometrical complexities. The fact 

that each airport has evolved local procedures to handle idiosyncrasies of the geometry, traffic 

characteristics, surrounding airspace design, controller culture at that facility, etc., creates the 

uniqueness. The need to provide advisories consistent with local procedures creates the need for 

complex adaptation.

Related Research

This section summarizes and provides references to relevant related research. Note that the 

program structure under which the SORM work was conducted has changed since this work was 

conducted along with a corresponding change in research focus. Included in this section are the 

research areas that were in place during the life of this concept development, and that are still

relevant to runway management.

Subsections 2.4.1–2.4.3 focus on NASA’s research within the ASP discussing how this research 

affects and is affected/influenced by SORM. The subject research focuses on specific domains 

and technology related areas. The final subsection (2.3.4) presents relevant non-NASA research 

which either sets the environment within which SORM must function or which may be leveraged 

to accelerate SORM research.
SORM Concept of Operations

11

Super Density Operations Research Area

A ConOps has been developed for Super Density Operations (SDO) (version 1), that serves as a 

guide for NASA’s efforts in researching capacity constraining issues in major terminal areas. 

The technical challenges cited in the SDO ConOps are worth noting: 

(1) enabling precision trajectories in dense terminal airspace; (2) defining regional 

resource optimization processes; (3) achieving robustness to varied and chaotic 

weather conditions; and (4) satisfying environmental considerations while 

enabling NextGen air traffic density projections. 

The JPDO ConOps identifies Super-Density Arrival/Departure Operations as one of eight key 

capabilities. The concept is multi-faceted and would require extensive description to adequately 

address it in its entirety. The following discussion will be limited to the framework of the 

concept and the applicability to the SORM process. 

The SDO ConOps identifies “key capabilities” envisioned for NextGen; those which relate to 

SORM are Aircraft Trajectory-Based Operations, Equivalent Visual Operations, and SuperDensity Arrival/Departure Operations. Specific focus of NASA’s research in the area of SDO is 

defined in five core areas: collaboration and coordination of objectives, robust capacity, 

increased efficiency, reduced environmental impact, and determination of roles and 

responsibilities. These SDO “core areas” mirror those identified in the JPDO ConOps: Capacity 

Management, Flow Contingency Management, Trajectory Management, and Separation 

Management. These are discussed in the context of the SORM work; the short descriptions

below of each of these elements are accompanied by brief comments regarding the consideration 

of a SORM capability. 

 Capacity Management assumes balanced capacity/demand (includes incorporation of 

delay absorption strategies) at the national level which permits SDO at the terminal 

level. The planning horizon defined is 1–6 hours for the short term and 6+ hours for 

the long term. 

o Envisioned SORM capabilities respond to short term and long term capacity 

predictions, as well as forecast weather. The specifics of the planning time 

horizons are to be determined for SORM.

 Flow Contingency Management is defined as “the process that identifies and resolves 

congestion or complexity resulting from blocked or constrained airspace.” It is 

assumed that resolutions will impact the management of runways, although it is not 

known exactly how or to what degree. 

o Coordination with proposed strategies will be necessary if an effective SORM 

capability is to be achieved.

 Trajectory Management is defined as the “process by which individual aircraft 

trajectories are managed just before and during the flight to ensure efficient individual

aircraft efficiency within a flow.” 

o Presumably “flow” has implications which include the airport surface 

environment; coordination of flows at this level is complex and the SORM 

vision is for an active role in this process. One of the premises of SORM is that 

a runway assignment provided several hundred miles from the airport may be 
SORM Concept of Operations

12

changed for a number of reasons. Although not envisioned to be a common 

occurrence, this would affect functions envisioned under Trajectory 

Management, e.g., precision spacing, and continuous descent approaches,

among others. 

 Separation Management according to the JPDO “ensures that aircraft maintain safe 

separation from other aircraft, from certain designated airspace, and from hazards 

(e.g., terrain, weather, or obstructions). 

o The SORM concept assumes that the appropriate separation standards, whether 

the responsibility of the flight deck or air traffic control, are maintained. As 

mentioned in a previous sub-section, the future may bring about changes in the 

separation standards in cases where there are wake considerations, or 

determined to be the absence of wake vortices. A SORM capability will 

consider these conditions and plan accordingly.

The SDO research area is considering many capabilities focused on efficiency and safety in 

airspace and surface operations. One of the significant SORM challenges is to determine when 

systemic or local interests are best served by providing recommendations that are contrary to 

operations that are currently planned. An example is an aircraft on a CDA (continuous descent 

approach), optimized for a specific runway, is when and aircraft is re-assigned to a different 

runway, a decision based on addressing surface congestion. The same example could hold true 

for an aircraft on a “precision spacing” clearance.

Safe and Efficient Surface Operations Research Area

The airport surface is arguably the most complex domain of the air traffic control system. Its 

geographical limitations provide a myriad of problems. Departure traffic is subject to many 

factors which adversely affect predictable schedules. Other variables include the following: 

servicing of aircraft, aircraft waiting for delayed passengers, weather, delays at the departure

and/or destination airports, and potentially during the enroute phase of flight. Depending on the 

available space on the surface, many airports have limited capabilities to absorb delays of 

departing aircraft outside the ramp areas. For these reasons, among others, the surface represents 

a highly complex traffic management problem and is the focus of efforts at NASA to address 

surface automation. Currently there is an ephasis on capabilities“to manage traffic on the airport 

surface (gates, taxiways, and runways) safely and efficiently to enable maximum throughput and 

capacity in the airport environment” (ref. 4).

The SESO research area is focused on efficiency of surface operations. To support this activity, 

a ConOps was developed; the remainder of this section addresses features provided in the SESO 

ConOps. The concept is based on three functionalities: a Spot Release Planner, Runway 

Scheduler (or Departure Scheduler), and a Taxi Scheduler. 

The over-arching model for these functionalities is the Complete Airport Optimizer (CAIRO) 

which models all operations on the surface. The Spot Release Planner generates a schedule for 
SORM Concept of Operations

13

“spot5release” that is intended to absorb delays at the “spots” rather that at the runway. This 

function is sub-divided into short term scheduling and long term scheduling, the latter providing 

for collaborative decision making inputs. The output of the Spot Release Planner is the ground 

controller. Longer-term usage includes the air route traffic control center which could use the 

information for metering arrival traffic. The Runway Scheduler manages operations on a single 

departure runway, this capability includes runway crossings and arrival aircraft in addition to 

departure aircraft. The Runway Scheduler takes inputs regarding “queue” characteristics, 

separation criteria, operational constraints on aircraft (ground delay factors, expected departure 

clearance times (EDCTs)), and others. The Runway Scheduler outputs assignment to departure 

queues, assignment of take-off times, and active runway crossing times. The Taxi Scheduler is 

intended to output conflict-free trajectories through use of required times of arrival and estimated 

departure queue entry times. The Taxi Scheduler integrates the Spot Release Planner and 

Runway Scheduler to output these solutions. The concept suggests benefits to deviation from the 

first-come, first-served FCFS paradigm. Alternatives to FCFS are proposed though the CAIRO 

model.

Significant interaction with the surface automation capabilities is assumed under the SORM 

concept. Due to the short planning horizon between when an aircraft is known to the system as a 

viable participant (ready to taxi6) in the traffic flow, until it arrives at the runway, there is little 

discretionary time. It is therefore assumed that the schedule generated by surface automation for 

departures cannot respond to adjustments.

Dynamic Airspace Configuration Research Area

The notion of dynamic configuration of airspace has been considered for many years. The 

current system operates on the paradigm of airspace segregation based on aircraft capabilities, 

services provided, and, in the case of the application of ATC services, the basic premise that a 

controller is responsible for a piece of airspace defined by horizontal and vertical dimensions 

(“sectors” in a radar environment). 

During periods of reduced traffic volume, one controller may assume responsibility for several 

sectors. There are formal provisions for “delegating” airspace, which may be required for many 

reasons. This is handled through intra-facility directives or letters of agreement between 

facilities. As traffic volume and operational complexity in the NAS increases, it is reasonable to 

say that greater flexibility in the management of airspace will be required. Research within the 

Dynamic Airspace Configuration research area focuses on exploring avenues for such flexibility. 

The objective of this work is to allocate airspace as a resource to meet demand while addressing 

weather, safety, security, and environmental constraints. In consideration of runway 

configuration changes, re-allocation of airspace may serve to permit a more “graceful” change to 

 

5 This refers to one of many such locations at large airports, found at the edge of the ramp area prior to entering 

active taxiways (boundary of the non-movement and movement areas) controlled by air traffic control. These 

“spots” are used to stage aircraft and control entry onto the active taxiways.

6 Aircraft usually are in contact with ramp control for the push-back unless the push-back affects the “movement 

area.” The movement area is defined as “the runways, taxiways, and other areas of an airport which are used for 

taxiing or hover taxiing, air taxiing, takeoff, and landing of aircraft, exclusive of loading ramps and aircraft parking 

areas” (14 CFR 139.3).
SORM Concept of Operations

14

a new configuration and facilitate more efficient operation to that runway. For this reason, 

information sharing between SORM and the appropriate entities tasked with future airspace 

allocation will be required. As CADRS capabilities are applied, further coordination may be 

required as flight paths could be affected.

Traffic Flow Management (TFM)

The systemic aspects of runway management proposed in the SORM concept are heavily 

dependent upon inputs from TFM on several levels. Greater detail regarding these 

considerations can be found in Section 5.0. In short, the systems approach proposed by SORM 

is centered on the notion that airports serve a larger network and that effective runway 

management is essential in this process. It follows that TFM considerations and constraints are 

necessary inputs to the runway management process, both in terms of runway selection and how 

the runways are used. It is envisioned that the use of Traffic Flow Initiatives will be a tool in the 

conduct of SORM capabilities.

Traffic Flow Management in the NAS is the responsibility of the FAA in the Systems Operations 

Services Unit of the Air Traffic Organization. Traffic management in the NAS is orchestrated by 

the Air Traffic Control System Command Center (ATCSCC) in coordination with TMUs located

at centers and major TRACON and ATCTs throughout the country. The ATCSCC manages 

traffic flows on a nationwide basis with the ultimate goal of balancing system demand with 

capacity. Traffic flow management issues that can be handled by the air route traffic control 

center (ARTCC) for issues within their airspace are managed at that level assuming there are not 

implications beyond the center bounds. There are several tools used by traffic flow managers to 

regulate the flow of traffic. These include Ground Delay Programs, miles-in-trail (MIT) 

restrictions, re-routes, arrival gate balancing (terminal boundary) for airports, among others. The 

avenue for providing TFM considerations and constraints, the way they impact runway 

management, and subsequently how they translate into the ways runways are used, are subjects 

for investigation.

Details of this work will not be discussed as the SORM concept assumes certain core 

functionalities for the TFM process. The particular strategies and functions, though interesting, 

are not necessary for the initial development of SORM capabilities. As future strategies and 

concepts are further defined, they will be addressed by SORM research.

Other Related Research Activities

The Deutsches Zentrum für Luft- und Raumfahrt (DLR), or German Aerospace Center, 

developed a concept which also considers both arrivals and departures for dual use runways 

(used for both arrivals and departures). The concept Coordinated Arrival Departure 

Management (CADM) combines inputs from the 4-Dimensional Cooperative Arrival Manager 

(4D CARMA) and the Controller Assistance for Departure Optimization” (CADEO) (ref. 8). 

Both 4D CARMA and CADEO are separate processes which optimize operations in their 

respective domains. Under CADM, an algorithm considers the traffic situation on the ground 

and in the terminal maneuvering area (analogous to the terminal area in the United States). Gaps 

or arrival-free intervals are identified in the arrival stream for insertion of departing aircraft. 

Where those gaps do not exist, the required action to create the gaps is calculated and presented 

to the controller for implementation.
SORM Concept of Operations

15

Tactical Runway Configuration Management (TRCM)

Introduction to TRCM

This section describes the Tactical Runway Configuration Management tool, an algorithm that

plans the runway configuration as well as other aspects of how the runway, airport, and airspace 

resources are used in aggregate, which we collectively refer to as the airport configuration. 

Today, airport configuration decisions are made manually. Air traffic personnel are able to plan 

runway configuration changes in response to changing weather conditions, as long as the weather 

is accurately forecast. However, they are less proactive in changing the runway configuration to 

accommodate traffic demand, because they do not have the requisite information that provides 

information concerning the benefit, and the additional workload required to affect the change. 

Without detailed, accurate traffic forecasts, and under high workload conditions, controllers 

infrequently change the configuration. As a result, the configuration must be adaptable to the 

variability in conditions that occur over an extended period of time. Significant opportunity 

exists to use available airport configurations more effectively to improve airport efficiency. 

Moreover, future technologies and operational concepts will require more complex airport 

configuration choices. Air traffic personnel will be unable to manually evaluate these choices 

unaided, further motivating research on automation such as the TRCM tool to support airport 

configuration management. The uniqueness of airports and the variation in procedures that have 

evolved from local issues and personalities presents a substantial challenge for airport 

configuration automation to be deployable and beneficial to any airport. While all airports must 

select the runway configuration, other aspects of airport configuration vary at different airports. 

Some airports (e.g., Hartsfield-Jackson International Airport (KATL)) select the departure split 

(i.e., mapping between runway and departure fix used to assign the departure runway); some 

airports (e.g., Los Angeles International Airport (KLAX)) choose between runway assignment 

rules based on either direction of flight or aircraft parking location; John F. Kennedy 

International Airport (KJFK) has a rigid departure runway assignment policy but must make 

other decisions related to airspace allocation within the New York metroplex; and many airports 

must decide how much runway capacity to allocate to arrivals and departures on a mixed-use 

runway. In many cases where such flexibility exists, a default decision is applied most or all of 

the time or a traffic manager makes the decision without any quantitative basis (i.e., based only

on experience). Optimally planning how the runways within a runway configuration should be 

used, or how other limited resources should be used, offers substantially larger benefits than 

optimally selecting only the runway configuration.

The TRCM airport configuration planner provides decision support over the next 90 minutes and

is intended for use by personnel in the ATCT, TRACON TMU, and ARTCC TMUs, who are 

responsible for, or are stakeholders in, airport configuration decisions. Eventually, the traffic 

managers will interact with TRCM by configuring parameters and objectives. A conceptual 

TRCM user interface that addresses the information commonly used by air traffic personnel in 

the runway configuration/usage decision making process has been developed. TRCM respects 

current air traffic procedures while being extensible to future operational scenarios and is 

capable of being easily applied to a wide variety of airports. In this way, the TRCM tool is a 

significant advancement in automation for airport configuration planning that could be 

implemented within the current NAS, while having increased benefit in NextGen. The TRCM 
SORM Concept of Operations

16

capability would be implemented as part of an airport automation system, such as the Tower 

Flight Data Manager (TFDM). 

It should be emphasized that TRCM is an advisory tool and does not change the roles or 

responsibilities of any recipients of the TRCM outputs. The TRCM capability will provide a 

deterministic output for the airport configuration schedule, although it will explicitly consider 

uncertainty internally. In a metroplex, TRCM plans coordinated airport configurations for each 

airport in the metroplex. The set of factors considered in selecting the best configuration 

schedule will include the traffic demand (which includes direction of flight and parking 

location), weather (e.g., wind speed, wind direction, ceiling, and visibility), environmental 

requirements (e.g., mandates that the configuration be rotated at some interval of time), TFM 

restrictions, and defined configurations and associated procedures. To select the optimal airport 

configuration, TRCM considers the effect on airport throughput, delay for departures to reach 

departure fixes and arrivals to reach parking gates, and efficiency (e.g., fuel burn). Note that a 

number of factors, such as the location of the aircraft’s parking gate, is considered implicitly by 

including the delay and fuel required. Beyond those described in this section, additional 

capabilities are envisioned for TRCM and the other elements of SORM. National Airspace 

System user input to the runway management process will eventually be considered in the 

SORM algorithms. User input, through the collaborative decision making process (ref. 9), has 

become a mainstay in the conduct of NAS operations. The avenues of such user participation in 

the SORM concept, and the processes most appropriate for that input, have not yet been studied.

Airport vs. Runway Configuration

Airport configuration planning may be under-studied in air traffic management research for 

several reasons including a perception that the problem is limited to runway configuration 

decisions and that controllers currently do a good job of making these decisions with manageable 

workload. Consequently, the need and potential benefits for providing an airport configuration 

decision-support tool (DST) has been overlooked. Past studies have shown that, unaided, 

controllers do not select the best time at which to make runway configuration changes (ref. 10)

and that airport delays are highly sensitive to the timing of the configuration change (ref. 11). 

For example, at the end of an arrival rush and the beginning of a departure push, waiting until 

runway departure queues have formed to switch to a configuration that favors departure capacity 

is too late. Controllers tend to use experience to make traffic management decisions. Observing 

historical operations helps controllers to select the best configuration to use. However, 

variations from day to day require detailed modeling to select the optimal configuration change 

time. The potential benefit for a DST to advise the runway configuration change time within 

current operations is sizeable at some airports.

In addition to runway configuration, aspects of airport configuration such as runway assignment 

policies must be managed to ensure that airport resources are used efficiently. For example, 

when Boston’s Logan International Airport (KBOS) operates in a runway configuration that 

lands arrivals on runways 22L and 27 and departs on runways 22L and 22R, the traffic manager 

must select between the standard operating mode, in which arrivals have priority to runway 22L, 

and the accelerated departure procedure, in which departures have priority to the mixed-use 

runway (ref. 12). This decision to balance arrival and departure delays must be made sufficiently 

in advance so that the arrivals may be managed by the center and TRACON accordingly. Many 

airports with mixed-use runways always give arrivals priority, when gaps for a certain departure 
SORM Concept of Operations

17

rate could be coordinated. In NextGen, increased use of mixed-use runways will make selecting 

the most efficient airport configuration more difficult to do manually.

While air traffic personnel do an excellent job given the information they have available and the 

other demands on their attention, there are potentially substantial benefits resulting from 

improvements to the use of less-than-optimal existing procedures. Even when the runway 

configuration decision appears to be straightforward, other airport configuration decisions must 

or could be made. Elements of airport configuration beyond runway configuration are often not 

explicitly controlled or decisions are made infrequently and reactively in response to traffic 

conditions. 

For example, although Dallas-Fort Worth International Airport (KDFW) is a large airport both in 

terms of the traffic volume and the number of runways, wind and preference are sufficient to 

select the runway configuration. The preferred runway configuration is South Flow7. When 

winds require, North Flow is used; a few times a year, strong northwest winds require a runway 

configuration in which runways 31L and 31R are both used for mixed operations. However, 

how efficiently the airport serves the traffic demand depends strongly on how the aircraft are 

assigned to the runways. The airport experiences strong directionality to the traffic due to its

geographic location and use as a hub. Runways are generally assigned based on direction of 

flight, and, consequently, delays can occur for one runway while another runway is 

underutilized. Dallas-Fort Worth has the procedural flexibility to change the set of departure 

fixes that are assigned to each runway (within constraints that ensure that no airborne crossing or 

merging can occur), in order to balance the demand for each runway and minimize overall

delays. This decision, not the selection of the runway configuration, determines how efficiently 

the airport will operate and requires an ability to predict departure queues and flight times 

relative to taxi times. The controllers currently have no automation to aid this decision.

Atlanta Hartsfield International Airport has a simple runway configuration with five parallel 

runways. Wind and preference are sufficient to determine whether the runways will be used in 

West Flow or East Flow. Runways 8R/26L and 9L/27R are used for departures and runways 

8L/26R and 9R/27L are used for arrivals. Runway 10/28 may be used for departures, arrivals, 

mixed operations, or not used at all. Consequently, there are four commonly used runway 

configurations in each flow direction. The taxi distance to/from runway 10/28 is much longer 

than to/from the other runways. As a result, the decision whether or not to use runway 10/28 

must consider both runway delays and taxi distance, which is not easy for a controller to 

optimize unaided. In addition, KATL uses departure splits to assign departures to the two or 

three departure runways, to avoid airborne crossing or merging. Figure 1 illustrates the standard 

departure split when three departure runways are used in West Flow; the departure fixes are 

shown as waypoint symbols. The departure fixes are shown based on a “north-up” orientation. 

Aircraft departing over the north and west departure fixes would be assigned runway 8R for 

departure, aircraft departing over the east fixes, runway 9, and those departing of the south fixes, 

runway 10. Similar to KDFW, several alternate departure splits, essentially radial lines from the 

 

7

In South Flow, arrivals use runways 17L, 17C, and 18R (13R is also available for arrivals but generally not 

needed), while departures use runways 17R and 18L. In North Flow, arrivals use runways 36L, 35C, and 35R 

(arrivals to 31R are also possible but demand generally does not require use of the diagonal runways), while 

departures use runways 36R and 35L (departures from 31L are also possible).
SORM Concept of Operations

18

airport that divide the departure fixes into two or three groups where each group is assigned to 

one of the runways, have been defined and may be selected to balance the demand on each 

runway. The departure split is one element of the KATL airport configuration, used to avoid the 

situation where a departure queue exists at one runway while another runway is underutilized. 

To use the runways as efficiently as possible for the forecast traffic, the runway configuration 

and departure split must be planned together. 

Figure 1. KATL baseline departure runway assignment procedures.

Airport vs. Runway Capacity

Most prior research on runway configuration management has adopted the airport capacity curve 

model first introduced by Newell (ref. 13) which describes the tradeoffs between arrival and 

departure capacities using a separate curve for each operating condition. Each runway 

configuration may operate in different conditions, for example using visual or instrument 

approaches, resulting in separate curves. Mixed-use runways, crossing or dependent runways, 

and required taxi crossings are some of the causes for the tradeoff. Gilbo popularized the curves 

and described a method for drawing the curves by fitting a line around observed traffic counts

(ref. 14). The curves may also be drawn based on theoretical maximum rates; the FAA’s 

capacity benchmark provides curves for 35 of the nation’s busiest airports.

Numerous people (Frankovich, Weld, Leihong, and Gilbo (refs. 15–18), for example) have built 

queuing models of the airport employing these capacity curves and then proposed various 

optimal methods for selecting the sequence of runway configurations and operating points (i.e., 

feasible combinations of arrival and departure rates) that best serve the forecast demand. While 

useful for strategic planning of traffic flow management initiatives, this approach is not sufficient 

for tactical runway usage decisions. Substantial variability exists in the realized capacities 

observed within a runway configuration, demonstrating that the capability of the airport to 

handle arrival and departure traffic is much more complex than represented by a single curve for 

each runway configuration.

Figure 2 plots the arrival and departure capacity pairs that were planned by the TMCs at KJFK at 

different times when the airport was operating in the same runway configuration, as recorded in 
SORM Concept of Operations

19

the Aviation System Performance Metrics (ASPM) database. The average arrival and departure 

capacity matches the airport’s standard capacity for this configuration. However, the airport’s 

planned capacity varies substantially from this average, and not only along the standard arrivaldeparture capacity envelope for the configuration. Note that the data points are not the actual 

arrival and departure counts, but the capacities that were planned to be used, for the purpose of 

traffic flow management decisions, when the airport was operating in that configuration. The 

capacity curve is too simple a model of airport capacity for tactical airport configuration 

planning. Moreover, ATCT controllers do not explicitly select arrival and departure rates or

manage traffic to achieve those rates. For Tactical Runway Configuration Management to be 

effective, it must communicate the arrival/departure tradeoff in a way that is complementary to 

current procedures. 

Figure 2. Planned John F. Kennedy International Airport arrival and departure 

capacities for different instances of runway configuration 31R/31L in visual 

meteorological conditions.

Furthermore, the capacity curves for different runway configurations are often not sufficiently 

distinct so that many different runway configurations appear equally efficient. Runway 

configuration planning approaches based on capacity curves, consequently, must also use 

information about local runway configuration preferences. In addition, prior approaches often

have used models for the cost to switch between configurations that are too coarse for tactical 

planning or require data that would be impractical to obtain and maintain for every airport and 

runway configuration for an operational system. Finally, the operating point, while useful for 

traffic flow management, does not easily translate into the tactical decisions controllers make. Airport Departure Rate (ADR) (operations/hour)

Airport Acceptance Rate (AAR)

(operations/hour)

AAR/ADR Pareto
SORM Concept of Operations

20

These approaches also fail to provide a system perspective, such as how a runway configuration 

and operating point choice might result in taxiway congestion that causes delays not related to 

the runways.

Many runway configurations involve an operationally important, but often unused, ability to 

trade-off between arrival and departure capacities. This tradeoff would be part of the airport 

configuration, specific to the runway configuration which entails specifying the airport operating 

point—the combination of arrival and departure rates that lie on or within the airport capacity. 

While this would accomplish the objective of managing the arrival/departure tradeoff and would 

be applicable at any airport, it would not provide an operationally meaningful advisory to 

controllers. Controllers would need to convert an output such as 12 arrivals and 17 departures 

during this 15-minute epoch, for example, into the actual decisions they make, which might be a 

runway assignment policy at some airports and an inter-arrival spacing policy at others. In 

TRCM, runway usage policies may be approximate, such as “keep arrivals off runway 18R” or

“only arrival overflow to runway 18R,” or they can be more precise, such as “10 MIT arrival 

spacing for departures.” Note that TRCM requires a limited number of discrete policies; it will 

not allow a policy such as “N MIT arrival spacing” and then optimize to find the best value for 

N. However, since operationally a limited number of options would be efficient (e.g., allow a 

departure between every arrival pair, allow a departure between every other arrival pair, allow 

two departures between every arrival pair, etc.), this constraint does not limit the TRCM

applicability or achievable benefits.

TRCM Algorithm

A variety of automation systems have been developed and deployed for individual airports to 

address specific airport configuration issues; none have been deployed more widely. For 

example, the Enhanced Preferential Runway Advisory System is used at Boston’s Logan 

International Airport to advise runway configurations to balance environmental impacts on an 

annual basis by suggesting alternative, lower-capacity configurations when weather conditions 

and demand permit. The Surface Movement Advisor was a custom solution developed for KATL 

to aid in the selection of the departure split to balance demand between the two departure 

runways (ref. 19).

The TRCM tool plans the airport configuration and presents this plan as an advisory to the 

ATCT and TRACON traffic managers who are responsible for airport configuration decisions. 

The foundation of the TRCM concept is the assumption that each of the individual decisions that 

comprise the airport configuration takes the form of a choice between a finite numbers of 

policies that are known in advance. The runway configuration, for example, is selected as one of 

a set of predefined runway configurations used at that airport. 

The TRCM algorithm efficiently searches the possible airport configurations and the times at 

which different elements of the configuration may be changed. As part of this search, the 

algorithm quickly models how aircraft would use the airport resources under possible airport 

configuration plans to produce metrics for that plan, which are compared to the metrics for other 

possible plans. Tactical Runway Configuration Management frequently will need to output 

multiple policy decisions, for example a runway configuration, a departure runway assignment 

policy applicable under that runway configuration, and an arrival taxi plan (such as whether to 

cross an active runway or use a longer taxi path that goes around the end of the active runway). 
SORM Concept of Operations

21

Some of these airport configuration decisions may be independent of others while some are 

coupled. The requirement to identify the best time to change the configuration creates a 

computational challenge for the algorithm.

Through planning the airport configuration, TRCM affects flights in aggregate. While an 

alternative concept would be for automation to individually plan each flight, flight-specific 

advisories are less likely to be accepted by controllers in the foreseeable future. As a result, 

TRCM’s concept is designed to more closely match how controllers currently do their jobs, 

simply adding decision support for decisions they currently make.

TRCM Adaptation

At different airports, the airport configuration determination consists of different decisions. 

Handling these differences without designing different versions of TRCM for each airport is a 

common challenge for airport traffic management automation. The fundamental TRCM goal—

selecting the airport configuration that will maximize overall efficiency of the runways, airport 

surface, terminal airspace, and interaction of the airport with the NAS—is consistent at all 

airports. Elements of the TRCM algorithm and software must also be consistent at all airports. 

Some airport configuration decisions and the ways in which controllers express those decisions 

are common across many airports, while some airports also have configuration decisions that are 

unique to that airport based on local considerations and constraints. This section describes how 

TRCM is adaptable to individual issues at different airports to provide a solution that is practical 

and deployable across airports, using common software.

The runway configurations that may be used at an airport, as well as any unique restrictions on 

the weather conditions in which each may be used, must be specified as adaptation data. 

Another common airport configuration decision at many airports is the departure runway 

assignment policy. This decision affects runway balancing, flight and taxi distances, and 

whether procedural airborne separation is provided or temporal coordination is required between 

operations on different runways. How the runway assignment decisions are made varies among

airports. The most common approach uses a mapping that assigns each departure fix to one 

runway. The airport may select between several of these mappings; each mapping must be 

defined in the adaptation data used by TRCM. The “Runway Assignment Example” section of 

this paper (section 3.6.2) presents an example. 

Another common airport configuration decision is how mixed-use runways (i.e., those that serve 

both arrivals and departures during the same time period) will be used. This decision, which can 

significantly affect airport delays, can take different forms at different airports and, currently, is 

often not explicitly managed, although procedures allow it to be. TRCM could select between 

policies that achieve different departure capacities by specifying the frequency with which 

departure slots should be left in the arrival stream. In this case, the adaptation data would simply 

list policies such as “a departure gap between every arrival pair” and “a departure gap between 

every other pair of arrivals.” The “Runway Usage Example” section of this document (section 

3.6.1) presents an example in which the form of the decision is to define a default policy that 

gives arrivals priority and an alternate policy that defines a dedicated arrival runway as the 

primary arrival runway and uses the mixed-use runway for overflow arrivals.
SORM Concept of Operations

22

While the TRCM approach requires applying local knowledge to define the airport 

configurations that are used at that airport, the approach allows a common algorithm to be 

deployed to any airport. In NextGen and metroplexes, the airport configuration will include 

additional dimensions such as the allocation of Belmont airspace between LaGuardia Airport 

(KLGA) and KJFK operations in the New York metroplex. The TRCM approach is not only 

flexible to how different airports and metroplexes currently operate, but adaptable to future 

changes in procedures and extensible to new aspects of airport configuration that may need to be 

selected in a NextGen environment.

Airport Configuration Definition

The definition of “airport configuration” will evolve as the TRCM capability matures and other 

NextGen technologies become available. Initially, airport configuration will consist of the

runways that are being used as the default runways and the ways they are being used. 

Eventually, airport configuration will include other decisions such as the airspace routings being 

used. Table 1 provides descriptions for airport configuration elements relevant to TRCM.

Table 1. Initial Elements of Airport Configuration

Airport Configuration Element Description

Default (or primary) arrival runways and default 

departure runways

Specifies which runways are primarily used for 

arrivals, which runways are primarily used for 

departures, and which are “mixed use” runways.

Runway procedures in effect Defines the rules that apply to operations on a 

runway, how arrivals and departures may use the 

runways, such as the required separation between 

operations on a runway or on dependent runways, 

whether or not LAHSOs are permitted, and what 

dependencies exist between parallel, crossing, or 

converging runways. Also includes runway 

assignment rules based on arrival/departure fix or 

parking location.

Planned operating point for airport Specifies the planned arrival and departure 

capacities.
SORM Concept of Operations

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Table 2. Future Elements of Airport Configuration

Airport Configuration Element Description

Planned arrival and departure runway capacities Specifies the planned arrival and departure 

capacities for each runway.

Default taxi plan Describes the primary plan for arrival and 

departure taxi routing.

Airspace structure Describes the airspace structure, such as arrival 

and departure fixes in use, what routes/trajectories 

are being used, what required navigation 

performance (RNP) level is required to use a 

route, and what regions of airspace are primarily 

used for what flows.

Traffic Management Initiatives at an airport What TMIs are in effect at the airport, such as 

approval request requirements or MIT restrictions 

on departures

Factors that Affect Airport Configuration

This section lists and discusses the factors that affect the airport configuration decision. Several 

components of weather are central to determining which airport configurations are feasible; these 

elements are described in 

Table 3.

Table 3. Weather Factors that Affect Airport Configuration

Factor Description

Wind speed and direction

As noted earlier, FAA Order 8400.9 sets forth 

limits regarding wind speed/direction and runway 

assignment. Further, aircraft may not land or 

takeoff if the cross wind or tail wind exceed 

certain limits, which are specified by the aircraft 

manufacturer and flight operator. Therefore, wind 

speed and direction determine which runways 

may be used if they exceed permissible 

thresholds. However, controllers do not know the 

exact limits for a particular aircraft and a pilot 

may be more conservative than his/her company 

allows. Wind also affects the capacity of the 
SORM Concept of Operations

24

runway, with stronger headwinds typically 

resulting in lower capacity.

Visibility and ceiling

Visibility and ceiling affect the procedures that 

may be used, such as whether visual approaches 

can be used or if instrument approaches are 

required. Most frequently, the procedures affect 

the feasible arrival and departure rates but not the 

runways in use. At some airports, the highest 

capacity configuration for instrument approaches 

is not the same as the configuration with the 

highest capacity during visual approaches.

Some airports only have Instrument Landing 

Systems (ILS) or precision approach procedures 

for some runways, reducing the set of feasible 

airport configurations during low visibility and 

ceiling conditions.

As a result of existing procedures, such as 

dependencies between closely-spaced parallel 

runways, the airport configuration may be 

selected to only use one of the runways.

Reduced visibility and ceiling can increase the 

frequency with which aircraft perform missed 

approaches, further reducing the realized arrival 

rate.

Runway condition

Whether the runways are dry or wet (either from 

rain or snow) affects the average runway 

occupancy time and, therefore, the feasible arrival 

rates. Reduced taxi speeds may increase the time 

required to taxi across active runways. Some 

procedures, such as LAHSO, may not be 

available, increasing runway dependencies and 

consequently reducing the feasible airport arrival 

and/or departure rates.

Precipitation

Current or recent precipitation itself does not 

affect the airport configuration; it may however 

result in longer runways being selected over those 

with less length since precipitation results in wet 

runways, may contribute to reduced visibility 

reduced braking effectiveness, and may be 

correlated with low ceilings all reducing capacity 

for each runway configuration.
SORM Concept of Operations

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Table 4. Non-weather Factors that Affect Airport Configuration

Factor Description

Time of day

Whether or not there is daylight or darkness affects the 

procedures that must be used. For example, controllers may 

not issue clearance for a departure to taxi into position and 

hold (now called “line up and wait”) at night, which slightly 

reduces the runway capacity. A second example is variations 

in the noise mitigation rules may affect what arrival and 

departure procedures may be used or what runway 

configurations may be used. For example, the Quiet and 

Silent procedures used at the San Francisco International 

Airport and the Metropolitan Oakland International Airport 

during night and early morning hours creates a dependency 

between the two airports such that total departure capacity 

must be shared.

Noise abatement rules and other 

environmental considerations

Noise abatement rules exist in a variety of different formats at 

different airports. Procedures at KBOS require the noise 

exposure on the surrounding communities to be uniformly 

distributed on an annual basis. Chicago O’Hare International 

Airport and KJFK procedures require the configuration to be 

changed at least every so many hours. Some airports have 

preferred configurations that should be used whenever the 

weather permits. 

Some noise abatement rules are effectively requests by the 

local government with little or no legal obligation by the FAA 

to comply. 

Arrival demand

The number of arrival flights and their earliest possible 

landing time (which will vary some by runway) must be 

considered when selecting the airport configuration. Several 

characteristics of each flight further influence the 

configuration decision, including the aircraft type, the arrival 

fix, and the planned parking gate. 

Aircraft equipage, such as ILS capability, which includes pilot 

certification, should be considered. In the future, the aircraft’s

RNP level may affect what routes may be used.

Departure demand Departure demand based on latest available information times 

for estimated departure times.

Table 3. Weather Factors that Affect Airport Configuration Continued
SORM Concept of Operations

26

Factor Description

Defined runway configurations

Currently, selection of the airport configuration is limited by 

the set of pre-defined runway configurations. Often, however, 

the set is large. In the future, even larger numbers of airport 

configurations may be pre-defined for specific situations. In 

the development of TRCM, we assume the set of 

configurations has been defined in advance.

Closures for maintenance, 

snow/debris removal, mowing 

near runway

Runways or taxiways may be closed for snow or debris 

removal, construction (which may be a few hours or several 

months), or due to mowing near the runway/taxiway. Closed 

runways may prompt a complete configuration change or may 

just prevent use of that runway for a period of time without 

changing any of the other runways in use. Closed taxiways 

may prompt a runway configuration change if the surface flow 

would be significantly altered.

Equipment outages

Equipment such as ILS and precision runway monitors

occasionally require planned or un-planned maintenance. 

Equipment outages may reduce the feasible rates or prevent a 

configuration or runway from being used.

TRCM System Design

The incorporation of “runway usage policies” is central to the system design. Examples of these 

include the ways in which runways will be used (arrivals or departures only, mixed use) and 

restrictions to runway usage, such as MIT for arrivals. These policies can be focused on capacity 

or driven by other objectives (e.g., to alleviate congestion on areas of the airport). Note the 

following example of how runway usage policies have to be considered by the TRCM algorithm. 

Runway configuration A using the default runway usage policy A1 may be more efficient than 

runway configuration B using its default runway usage policy B1. Runway configuration B with 

alternate runway usage policy B2 may be superior to runway configuration A under any of its 

runway usage policies. Consequently, TRCM cannot first select the runway configuration and 

then select the runway usage policy or any dependent element of airport configuration as a 

separate step. Rather, TRCM must separately consider each airport configuration—every 

combination of runway configurations and the other policies defined for that runway 

configuration. This creates a larger number of configurations that must be evaluated. A large 

number of distinct runway usage policies for a runway configuration could create a 

computational problem for the algorithm. In practice, knowledge of the situations for which 

each policy might be used will allow heuristics to reduce the set of configurations that must be 

evaluated in detail, although these heuristics may require additional adaptation data based on 

expert, local knowledge. Furthermore, the runway configuration and runway usage decisions 

may be changed at different frequencies. While changing runway configurations may be 

Table 4. Non-weather Factors that Affect Airport Configuration Continued
SORM Concept of Operations

27

expensive in terms of lost capacity, there often will be little or no cost to change between runway 

usage rules. Changing the runway usage policy several times without changing the runway 

configuration may be efficient. Tactical Runway Configuration Management considers the cost 

to make the suggested airport configuration change. Different limits on the frequency of various 

airport configuration changes are also allowed.

Runway configuration and runway usage are also planned at different time horizons. Runway 

configuration may be planned 45 minutes in advance, while runway usage may not need to be 

fixed as far into the future. In some cases, the center might need to know whether the arrival rate 

should be reduced 30 minutes before the landing time of the affected arrivals. To manage 

arrivals, the TRACON will need to know 15 minutes before arrival runway assignment rule 

changes are to take effect. Departure runway assignment rules may be changed as aircraft block 

out from their parking gates. Consequently, TRCM must use different “freeze” horizons8for 

each type of decision since significant changes require more advance notice than minor changes.

Searching for not only the best airport configurations but also the time at which the configuration 

should change creates a very large search space. To operate in real-time, the TRCM algorithm 

makes several assumptions that may be relaxed as computational performance is measured and 

the algorithm matures. First, although the movement of flights is modeled in continuous time, 

the algorithm considers configuration changes at five minute intervals. This assumption is likely 

consistent with how TRCM would be used operationally. Second, each iteration of the algorithm 

searches for a single airport configuration action to add a new configuration change, to remove a 

previously planned configuration change, or to shift a previous configuration change to a 

different time. Multiple configuration changes are possible within the TRCM planning horizon 

through multiple iterations of the algorithm for overlapping time horizons. 

The TRCM algorithm operates every five minutes, which is a parameter that will be tuned based 

on computational loading. Each time the algorithm runs, if a configuration change is 

recommended, the change produced becomes part of the baseline configuration plan. After 

multiple passes of the algorithm, a sequence of configuration changes can be planned. This 

approach helps to incorporate updated information that would not be available if the algorithm 

ran once every 30 minutes. However, this approach creates some risk that the algorithm could be 

sensitive to the input data changing slightly for every pass and the results flipping back and forth 

rather than settling on a stable plan. 

To address solution stability under uncertainty, the TRCM algorithm employs an internal Monte 

Carlo approach. Consider the KLAX situation where departures may be assigned to a runway 

based on the departure fix mapping (called “taxi right”) or to the closest runway (called “taxi 

easy”). Under the “taxi right” mode, procedures ensure that there will be no airborne conflicts, 

and departures from the two runways may occur asynchronously without any coordination in 

time. Under the “taxi easy” mode, some aircraft assigned to the left runway will need to turn 

right, and some aircraft assigned to the right runway will need to turn left. If there is no 

departure on the right runway when the right-turning aircraft from the left runway is ready to 

takeoff, there is no departure delay. However, if there is an aircraft on the right runway, then the 

two departures must be coordinated in time, requiring one aircraft to be delayed. “Taxi right” is 

 

8 A freeze horizon defines that point beyond which a decision will not change.
SORM Concept of Operations

28

always more efficient during heavy traffic. During light traffic, whether “taxi easy” is more or 

less efficient than “taxi right” depends on the relative timing of flights reaching the two runways, 

which is uncertain and somewhat random. TRCM will use knowledge of the uncertainty to 

generate a number of scenarios for the aircraft runway times and will then solve the airport 

configuration problem for each possible traffic scenario and select the decision that is adaptable 

to the uncertainty. 

TRCM Problem Description

This section describes the mathematical formulation of the TRCM algorithm. An instance of the 

TRCM problem is defined by a set of flights, F, representing all arrivals and departures predicted 

to operate at the airport or metroplex from the current time through a specified modeling horizon. 

Tactical Runway Configuration Management is defined on a continuous time scale; it is assumed 

that the current time has been normalized to zero. Parameters hf and hp are the freeze and 

planning horizon, respectively; both are assumed to be greater than zero. No new configuration 

changes can be scheduled prior to time hf or after time hp. In addition, any configuration 

changes scheduled between the current time and hf cannot be canceled. In general, hf and hp

may be different for each airport configuration element, such as runway configuration and 

runway assignment policy.

Assume that a maximum number, M, of configuration changes are allowed between hf and hp. 

The set of configurations is indexed by k ∈ {1,2, ... ,K}. There are two sets of decision variables 

defined for each configuration k. For each, 1 ≤ m ≤ M, Δmk is a binary decision variable equal 

to 1 if the m’th configuration change is to configuration k and equal to zero otherwise. τmk is a 

continuous variable that is equal to the time of the m’th configuration change when Δmk = 1 and 

equal to zero otherwise. Define the matrices Δ = [ Δmk ], which contains all binary decision 

variables, and τ = [ τmk ], which contains all configuration change time decision variables. 

Define π to be the information state of the airport at the current time. The information state 

includes weather forecasts, scheduled configuration changes up to the freeze horizon, scheduled 

TMIs, runway and taxiway closures, and any other information affecting the operation of the 

airport.

minimize C(F, π, τ) (1)

s.t. hfΔmk ≤ τmk ≤ hpΔmk ∀m, k

τm′k

′ − τmk ≥ Bkk′ − (1 − Δm′k′Δmk)B̅ ∀m, k, m′ > m, k

′ ≠ k

∑Δmk ≤ 1 ∀m

k

∑Δmk ≥ ∑Δm+1,k ∀m

k k

Δmk + Δm+1,k ≤ 1 ∀m, k

τ ∈ A(π)

Δmk ∈ {0,1} ∀m, k

The objective function C(F, π, τ) is a generalized expected cost function over the set of flights,

F, given information state π and configuration change time decision variables τ. Potential cost 

metrics include flight delays, flight and taxi times, and fuel burn. The first constraint ensures 
SORM Concept of Operations

29

that each configuration change time is nonzero if and only if the corresponding binary decision 

variable is set to 1 and any nonzero configuration change time falls between the freeze horizon 

and the planning horizon. The second constraint requires a separation of Bkk

′ between 

configuration changes to configuration k and to configuration k

′

. This allows different 

configuration pairs to have different restrictions on how frequently changes may be made. For 

example, the direction in which the runways are used may be changed infrequently, while adding 

or removing a runway operating in the same direction can be done more frequently. Constant B̅

is defined large enough so that this constraint is inactive when either Δm′k

′ or Δmk is zero. The 

third constraint ensures that at most one configuration is chosen for each configuration change. 

The fourth constraint condenses the configuration changes by allowing a (m + 1)’th 

configuration change only if an m’th configuration change has been selected. The fifth 

constraint does not allow consecutive configuration changes to the same configuration. Define 

A(π) as the feasible space for configuration change times based on the current information state. 

Thus, the sixth constraint allows for airport- and scenario-specific constraints such as noise 

abatement procedures or resource usage restrictions. The final constraint defines the Δmk to be 

binary variables.

The binary variables and the non-linearity of the second constraint in the above formulation 

imply that the state space is non-convex. In addition, the expected cost function C(F, π, τ) will 

be difficult or impossible to compute directly due to the complexity of predicting flight 

operations. Therefore, a solution heuristic that makes a few simplifying assumptions should be 

defined.

First, replace the cost function C(F, π, τ) with a simplified cost function C̃(F, π, τ) that can be 

computed via fast-time simulation. Any such function can be plugged into the solution heuristic. 

A fast-time simulation model, however, will be dependent on deterministic gate and fix times for 

arrivals and departures, respectively. In reality, there is a significant amount of error in flight 

time predictions. This uncertainty can be accounted for by adding a Monte Carlo sampling 

scheme to the model. Error distributions are defined for the pushback times of departures and 

the fix crossing time of arrivals. A sample flight list is created by drawing a sample from the 

appropriate distribution for each flight in flight list F and applying that error to the flight’s gate 

or fix time. Let Fi be the i’th sample flight list. If N samples are drawn, then the objective 

function in the TRCM problem formulation is replaced with

minimize 1

N

∑ C̃(Fi

, π, τ)

N

i=1

(2)

The second simplification of the heuristic is a discretization of the state space. Assume that 

configuration changes can only be scheduled at predetermined times through the planning 

horizon and assume that configuration changes will only be planned at five-minute intervals. 

Future work will study removing this restriction, possibly through a second stage of the 

algorithm. To simplify implementation, also assume that the planning horizon falls on such an 

interval. Given π, the possible configuration list may be reduced using heuristics. For example, 

configurations only allowed under visual meteorological conditions do not need to be considered 

when the weather will be instrument meteorological conditions.

The above simplifications allow for a basic enumerative search to be used to solve the TRCM 

problem. The TRCM search heuristic is a recursive search algorithm. Each recursive call to the 

algorithm adds a new configuration change to the end of the list of configuration changes. The 
SORM Concept of Operations

30

algorithm maintains a single best global solution (Δ

∗

, τ

∗

) at all points in the algorithm and at all 

depths of the recursion. The algorithm is seeded with the solution Δ = τ = [0] for all m and k, 

which corresponds to no new configuration changes, and with the current best objective function 

value z

∗

equal to infinity.

TRCM_Search(Δ, τ, Δ

∗

, τ

∗

, z

∗

) (3)

Evaluate z =

1

N

∑ C̃(Fi

, π, τ)

N

i=1

.

If z ≤ z

∗

then set Δ

∗ = Δ, τ∗ = τ, and z∗ = z.

Let m be the smallest value for which ∑k Δmk = 0. If no such m exists then return 

(Δ

∗

, τ

∗

, z

∗

) and exit.

If m = 0 then set t = hf. Else set t to be the first interval time after the (m − 1)

th

configuration change time.

For each configuration k:

Set Δmk = 1. 

For each interval time t

′

from t to hp:

Set τmk = t

′

.

If τ is a feasible set of configuration change times then recursively call 

TRCM_Search(Δ, τ, Δ

∗

, τ

∗

, z

∗

) and set (Δ

∗

, τ

∗

, z

∗

) to the returned 

values. 

Set Δmk = τmk = 0.

Return (Δ

∗

, τ

∗

, z

∗

) and exit.

The above algorithm will return the optimal set of configuration changes over the planning 

period relative to objective function 1

N

∑ C̃(Fi

, π, τ)

N

i=1

subject to the constraints of the original 

TRCM problem over the discretized state space. In operation, the algorithm runs at a periodic 

rate such that there is significant overlap in the planning windows from one iteration to the next, 

each iteration beginning with the prior best solution.

Evaluation

Runway Usage Example

Memphis International Airport (KMEM) frequently operates in one of two equivalent runway 

configurations: arriving on runways 18R/36L and 18L/36R and departing on runways 18C/36C

and 18R/36L. Selection of the North Flow or South Flow configuration depends on the wind and 

traffic characteristics. KMEM serves both a large cargo operation and a passenger operation 

with separated ramp areas. Which ramp area the majority of the traffic is taxiing from/to is 

considered when selecting the runway configuration to reduce taxi distances.

To avoid departures crossing in the air, KMEM uses a rigid departure runway assignment rule 

based on the flight’s departure fix. All flights headed to the west are assigned to runway 

18R/36L, while all departures headed to the east are assigned to runway 18L/36R. Most 
SORM Concept of Operations

31

mornings, between 1300Z and 1500Z, a cluster of flights depart to the west, which requires them 

to be assigned to runway 18R/36L. This departure push overlaps a period of steady arrivals. 

The KMEM procedures allow the TRACON to assign arrivals to either arrival runway. 

Currently, most TRACON controllers do not consider the departure traffic when assigning 

arrival runways. To minimize flight time and their own workload, controllers assign arrival 

flights to the runway closest to the flight’s arrival fix. Occasionally during light traffic, 

controllers will consider where the aircraft will park on the airport. During this period of time, 

many of the arrivals are from the west and are assigned to runway 18R/36L. The arrivals are 

given priority and the departures form a long queue at 18R/36L waiting for infrequent, random 

gaps in the arrivals sufficient for a departure, while runways 18L/36R and 18C/36C are 

underutilized. 

When KMEM is in one of these runway configurations, TRCM advises how the arrival runways 

should be used. Three runway usage policies are defined: 

 Assign arrivals to the runway closest to their arrival fixes

 Assign arrivals to the runway that minimizes their combined flight and taxi times

 Use 18R/36L as an overflow arrival runway only after 18L/36R is full 

While not explicitly defined in the KMEM Standard Operating Procedures, the third policy is 

similar to how KJFK operates; KJFK identifies a primary arrival runway and an overflow arrival 

runway in each of its two-arrival-runway configurations. Note that the second policy requires 

TRCM to model each flight all the way to its parking gate for each possible runway assignment 

to determine which runway to select. The third policy requires TRCM to model all of the traffic 

to know when delays would start to occur on the primary runway such that the overflow runway 

should begin to be used. The TRCM output specifies which policy should be used and the period 

of time for which it should be used, the format of which is consistent with current controller 

decisions; no procedural changes are required. 

Tactical Runway Configuration Management was tested using 62 flights that landed or departed 

during 1400–1530Z on September 9, 2010. Thirty of the 43 departures were departing to the 

west; 10 of 19 arrivals approached from the west. Airborne and surface surveillance data was 

used to determine the actual controller policy, which was “assign arrival runway based on 

direction of flight” for the entire time period. Tactical Runway Configuration Management

advised using 18L as the primary arrival runway for the entire time period, sending arrivals to 

18R only if 18L was being fully used. The TRCM and actual controller runway usage policies 

were simulated and the metrics compared. The simulation considered flying time, runway delay, 

and taxi time. The TRCM-selected policy reduced the total delay for arrivals and departures to 

22.6 minutes from 45.0 minutes under the controller’s policy. Under the TRCM policy, the 

arrivals experienced slightly more delay than under the controller’s actual policy due to a longer 

flying distance and slight runway delay. However, departures experienced substantially smaller 

delays on average. While only for a single traffic sample, this example demonstrates the 

significant benefit possible with airport configuration management. 

Runway Assignment Example

Orlando International Airport KMCO) has four parallel runways oriented north-south. From 

west to east, they are 36L/18R, 36R/18L, 35L/17R, and 35R/17L. The terminals are between the 
SORM Concept of Operations

32

36/18 pair and the 35/17 pair and consist of four separate terminal buildings. In south operation, 

arrivals use the outer runways 36L and 35R, and departures use the inner runways 36R and 35L. 

In north operation, during “severe clear” weather (basically, few or no clouds and unrestricted 

visibility), arrivals land on runways 36L and 35R (the outboard runways); runways 36R and 35L

are used for departures. 

The airport operates in two distinct modes. During heavy traffic, departures are assigned to 

runways based on direction of flight to avoid airborne conflicts; no coordination is required 

between the two departure runways. This mode is called “taxi for direction [of flight].” During 

light traffic, the “taxi for convenience” mode allows departures to be assigned to the departure 

runway closest to the aircraft’s parking gate regardless of the direction of flight. In this mode, 

the local controllers9 must coordinate releasing aircraft from the two runways to avoid conflicts 

in the air, and comply with the wake vortex separation requirements, because the flight paths 

may cross or merge. The delay at the runway to implement this coordination is small; since 

traffic is light, departures queues do not accumulate.

The SOPs indicate that the supervisor or controller in charge should select which procedure to 

use. As traffic level increases, there is a cost to using “taxi for convenience” because the small 

runway delays required to coordinate the runways begin to also delay subsequent flights as a 

queue forms. However, controllers often switch to “taxi for direction” well before the true 

efficiency crossover point. Some controllers prefer “taxi for direction” at all times to reduce 

workload. Some controllers “taxi for convenience” excessively, causing flights to be delayed 

more than they would under the “taxi for direction” procedure; TRCM can advise when each 

runway assignment procedure should be used.

Table 5 shows the taxi distance from each terminal to each departure runway. Assuming a 

nominal taxi speed of 15 knots, each 1000 ft. of taxi takes about 45 seconds. Therefore, runway 

35L is more than seven minutes farther than runway 36R from terminal 1. The difference in 

flight distance is relatively small in terms of time. The departure runways are separated by 8500 

ft, which is only about 30 seconds of flying time.

Table 5. Approximate Taxi Distances from Ramps to Departure Runways

Runway 36R Runway 35L

Ramp 1 (north–west) 8300 ft 18,200 ft

Ramp 2 (north–east) 14,600 ft 10,200 ft

Ramp 3 (south–west) 4500 ft 12,100 ft

Ramp 4 (south–east) 9500 ft 7100 ft

Thirty-eight departures from 1055Z to 1155Z on October 13, 2010 were studied (taken from 

 

9 The “local” controller is responsible for traffic using the runways and in the immediate vicinity of the airport.
SORM Concept of Operations

33

actual traffic data). Eleven of 17 flights from the west terminals and 10 of 21 flights from the 

east terminals departed to the east. The airport operated in the North Flow configuration with 

departures using runways 36R and 35L. Based on analysis of airport surface surveillance data, 

the actual operations were “taxi for direction” throughout the time period. Tactical Runway 

Configuration Management considered the two runway assignment policies, including the 

possibility of changing the policy during the time period. The TRCM algorithm advised that 

“taxi for convenience” should be used for the entire hour. The policies used historically and 

advised by TRCM were simulated and metrics compared.

Table 6 summarizes the simulation results. “Taxi for convenience” results in slightly longer 

runway delays because of the need to wait for traffic on the other runway that will cross or 

require merging. However, “taxi for convenience” produces a significantly smaller delay 

overall. This delay reduction comes primarily from shorter taxi times; the flight time to the fix 

from each runway is nearly the same. This example illustrates the potential of TRCM to provide 

significant benefit within existing procedures as well as the importance of measuring all phases 

of aircraft movement between parking gates and departure/arrival fixes. Future work will 

expand TRCM to consider fuel burn, workload considerations due to required coordination, and 

other metrics in addition to aircraft transit time.

Table 6. Tactical Runway Configuration Management Results at Orlando International 

Airport

Taxi for Direction 

(Actual Controller 

Decision)

Taxi for Convenience 

(TRCM Output)

Total delay 41.4 min 16.5 min

Average runway delay (per 

flight) 24 sec 26 sec

Runway Configuration Examples

Tactical Runway Configuration Management is also capable of planning the runway 

configuration and when to change it. To illustrate, a one-hour period of traffic from KJFK on 

March 19, 2009 was studied. Forty departures and 24 arrivals operated during the time period 

from 2:30 to 3:30 PM local time, which contained a wind shift at 3:00 PM that exceeded the 

tailwind threshold for runways 22L and 22R.

The actual runway configuration changed from runway 13L, 22L | 13R to 4R | 4L, 31L at 3:00 

PM.

10

 The TRCM algorithm selected the same initial and second runway configurations and 

advised the change to be made at 2:51 PM. This example supports that controllers are currently 

able to select runway configurations and TRCM is able to replicate these selections. In addition, 

TRCM planned which flights would be the last to use the first configuration and first to use the 

new configuration. 

 

10 The data source used to provide the actual runway configuration was limited to 15-minute resolution. 
SORM Concept of Operations

34

Tactical Runway Configuration Management does not always select the same runway 

configurations as were historically used. On June 24, 2009, according to ASPM data, KJFK 

changed from runway configuration 22L, 22R | 22R to 22L | 22R, 31L at 3:00 PM as demand 

shifted from heavier arrivals to heavier departures. For this traffic scenario, TRCM was seeded 

with the actual initial configuration. The TRCM algorithm advised changing the configuration to 

13L, 22L | 13R immediately and then to 4R | 4L, 31L at 3:37 PM. Both runway configuration 

schedules were simulated for 79 flights between 3:00 and 4:00 PM and the metrics compared. 

The TRCM configuration plan achieved 245 minutes of total delay, as opposed to 360 minutes of 

delay for the runway configurations actually used. TRCM’s initial configuration change 

provides independent arrival and departure runways, rather than a mixed-use runway. The later 

change to a configuration that favors departures reduced arrival delays before departure queues 

started to form. This example, while suggesting that planning runway configurations and change 

times may provide benefit, suggests that shadow-mode testing is needed to discuss with 

controllers why they would make certain decisions, possibly leading to enhancement to TRCM 

to ensure operational acceptance.

TRCM Benefit Mechanisms

In addition to the examples already described, the TRCM concept provides or enables a large 

number of operational improvements compared to current operations, as summarized in Table 7.

Table 7. Tactical Runway Configuration Management Benefit Mechanisms

Current Operations Impact of TRCM

Controllers currently change airport configuration 

reactively (e.g., after observing a departure queue 

form).

Airport configuration changes are planned in 

advance, considering both traffic demand and 

weather forecasts. Scheduling multiple future 

configuration changes supports other traffic 

management systems.

Controllers sometimes have difficulty planning 

the last aircraft on the old configuration and the 

first aircraft on the new configuration. Errors 

result in either aircraft needing to be rerouted to a 

different runway or runways being idle longer 

than necessary.

TRCM uses accurate estimated time of arrival 

predictions to plan which aircraft will be the last 

to use each runway in the old configuration and 

the first to use the new configuration.

Airport configurations are changed infrequently 

due to high manual workload and lost capacity 

during the change.

Automation helps to plan and coordinate 

configuration changes, enabling more frequent 

changes. TRCM considers the cost (i.e., lost 

capacity) of changing the configuration.

Airport configurations must handle a wide range 

of conditions.

New airport configurations may be defined for 

specific situations and applied tactically for short 

periods of time.
SORM Concept of Operations

35

Current Operations Impact of TRCM

Runway configuration is the primary decision.

Airport configuration encompasses runway 

configuration and other decisions about how the 

airport operates, such as standard taxi plan, 

airspace configuration, and runway assignment 

procedures.

Manual coordination of resources shared within a 

metroplex required. Procedures used to decouple 

airports.

TRCM plans metroplex configuration including 

airport configuration for each airport. Resources 

are dynamically assigned to different airports to 

match capacity with demand and provide highest 

efficiency for highest demand at that time.

Rigid procedures result in a long departure queue 

at one runway while another runway is 

underutilized (and holding at one arrival fix while 

other fixes are underutilized). Flexibility 

available in current procedures is not fully used.

TRCM selects between procedures currently 

allowed at that airport to balance runways and 

avoid surface congestion and other sources of 

inefficiency.

Lack of information and DSTs result in 

controllers making airport configuration decisions 

based on a single or limited objective(s) (e.g., 

arrival capacity).

Multi-objective optimization considers the effect 

of airport configuration on runway delays as well 

as surface congestion and airspace efficiency.

Operating point (i.e., combination of arrival and 

departure rates) is not coordinated between the 

TRACON and ATCT. TRACON gives priority to 

arrivals with limited awareness of departure 

delays or surface congestion. ATCT departs 

aircraft opportunistically with poor predictability 

of departure rate.

TRCM communicates optimal arrival/departure 

tradeoff. Frequent operating point changes allow 

airport resources to be dynamically matched to 

time-varying demands.

Controllers perceive additional flight time as 

making an additional taxi time to a runway with a 

shorter queue not beneficial.

Automation determines the runway assignment 

policy that optimizes over all of the factors that 

influence airport and individual flight efficiency.

Summary of the TRCM Concept and Algorithm Development

NASA’s TRCM research to date has succeeded in advancing the recognition within the research 

community that the problem of efficiently scheduling the airport configuration is broader than 

planning the runway configuration, and that the near-term potential benefit for airport 

configuration planning is substantial, and the future need is even larger. An algorithm that 

implements the TRCM concept producing optimal airport configuration schedules has been 

developed and tested through fast-time simulations. An in-situ evaluation of this algorithm (site 

adapted) has been conducted at KMEM by the FAA in early 2014. The data from this evaluation 

is currently being analyzed. To complement the decision support tool, a conceptual interface has 

been developed.

Table 7. Tactical Runway Configuration Management Benefit Mechanisms Continued
SORM Concept of Operations

36

The TRCM concept calls for automation to plan runway configuration at an airport as well as 

other airport configuration decisions, such as runway assignment policies, runway usage 

procedures, and airspace allocation within a metroplex, depending on the decisions that must be 

made at the particular airport. The algorithmic approach uses common software with local 

adaptation data to accommodate existing variations between airports while being flexible to 

support new decisions as required under NextGen concepts. Moreover, the approach outputs 

operationally meaningful advisories; controllers do not need to translate the outputs into the 

actual decisions to be made.

The algorithm selects the elements of airport configuration by first considering forecasts for 

weather and other conditions to determine feasible choices. The algorithm then uses fast-time 

modeling to predict how the forecast demand would be served by the runways and other limited 

resources under each possible configuration schedule to identify which configuration schedule 

will maximize the airport and terminal area efficiency. The output includes the sequence of 

airport configurations and the times at which the configuration should be changed. Different 

elements of airport configuration are allowed to change at different maximum frequencies. The 

algorithm’s objective function currently considers overall delays for arrivals to reach their 

parking gates and departures to reach enroute airspace, not just runway delays. The cost for 

changing the configuration is modeled through reduced capacity during the change and varies for 

different configuration changes. Preferences for certain runway configurations that capture 

aspects of the decision not currently modeled, such as the noise footprint of resulting flight paths, 

can also be considered by the algorithm. Future enhancements will allow the objective function 

to consider additional factors such as fuel efficiency, environmental impact, and operator 

preference in addition to delays. The algorithm simultaneously optimizes runway configuration 

and the other airport configuration decisions since selecting the runway configuration first, 

assuming the default runway usage policy, could result in an overall solution that is sub-optimal. 

The algorithm currently runs on a standard laptop computer sufficiently fast to be used within a 

real-time decision-support system and does not require any expensive software licenses to solve 

the optimization problem. Heuristic techniques are used to reduce computation time, which 

could be relaxed with more powerful computational resources.

Results from evaluations using real-world examples and data have shown that significant 

benefits are possible by using current procedures more efficiently. Examples using several 

airports demonstrated that the proposed automation could have achieved valuable delay 

reductions as compared to actual historical operations. Allowing changes to current procedures, 

for instance at airports that currently do not provide runway balancing control through runway 

assignment policies by reducing workload concerns through decision support, would deliver 

larger benefits. In addition, many other automation systems require the airport configuration that 

will be used as input data; the described algorithm could be used to provide that information.

Continued research is focusing on extending the airport configuration planning concept and 

algorithm to metroplex and NextGen environments. The dependencies between airports within a 

metroplex create a requirement to simultaneously consider the airport configurations at each 

interdependent airport in order to minimize airport interactions and allocate resources between 

the airports to best achieve efficiency across the entire metroplex. Tactical Runway 

Configuration Management will be able to advise what airport and airspace configuration would 

be more optimal to use.
SORM Concept of Operations

37

Additional areas of study include TRCM operating in possible NextGen environments;

identifying new airport configuration decisions that would need to be made, and how effectively 

TRCM can advise these decisions; and the additional benefit possible if procedures related to 

airport configuration decisions currently available at some airports were made available at 

additional airports.

NASA has transferred the developed software to the FAA’s Surface Trajectory-Based 

Operations project, which is developing and field-testing various advanced airport automation 

concepts for integration into current and future ATM systems. 
SORM Concept of Operations

38

Strategic Runway Configuration Management (SRCM)

SRCM Overview

At the beginning of the SORM research effort, SRCM was an entirely un-studied area—the 

interaction between TFM and airport traffic management. Since that time, NASA has begun 

other research efforts in this area. The TFM process currently only considers airport arrival 

capacities when planning TMIs and does not consider the interaction between capacities at 

different airports (outside of metroplexes).

Although controllers and traffic managers at and near an airport only need to plan the schedule of 

airport configurations 90 minutes or less into the future, traffic management specialists in the 

ATCSCC and traffic management coordinators in the ARTCC require predictions of the airport 

capacity several hours in advance. At this time interval, these traffic management decision 

makers do not need to know the actual airport configuration. The essential information is the 

resulting capacities (for the combined terminal environment and airport surface, not just runway 

capacities) for use in planning strategic TMIs.

11 Further, system users, in particular the airlines, 

would benefit significantly from a capability that would reliably predict runway configurations in 

the planning of resources.

Strategic Runway Configuration Management will be a piece of automation (i.e., software 

implementing a set of algorithms) residing within some larger ATM system. The SRCM 

capability could be implemented with TRCM in an airport-based system such as TFDM or 

within a TFM System (TFMS). Strategic Runway Configuration Management will receive a 

variety of information from other automation systems such as forecast traffic demand, forecast 

weather at the airport, descriptions of the airport’s available configurations, and planned TMIs. 

This is expected to be the same data used by TRCM. These inputs may be stochastic. 

The outputs of SRCM will be displayed to traffic management specialists in the ATCSCC 

through the displays of their existing TFM automation systems. In addition, SRCM outputs may 

be displayed to traffic management coordinators in ARTCC TMUs as well as the TRACON and 

tower. The role of the traffic management specialists and TMCs will not change as a result of 

SRCM. Each user will continue to make traffic management decisions to balance demand with 

airport arrival capacity.

At single airports, a separate SRCM instance would operate independently for each airport, 

planning the configuration schedule and converting this plan to a capacity schedule. In a 

metroplex, a single SRCM would provide a coordinated plan for the capacities at each airport.

For example, if an airport in a metroplex environment has experienced significant delays due to 

weather, consideration would be given to this airport to maximize capacity, possibly at the 

expense of other airports in close proximity. For both metroplexes and single airports, NAS 

priorities would be considered in determining configurations and capacities for each airport.

 

11 At one hour in advance, knowledge of the specific configuration may be used to select the specific TMIs, with 

consideration for the operational challenges associated with each configuration. For example, some configurations 

may be more adaptable to weather uncertainty and, therefore, more reliably provide the forecast capacity. These 

factors are included in the TMI decision making process, albeit in a qualitative manner.
SORM Concept of Operations

39

Strategic Runway Configuration Management is distinct from TRCM due to the different 

characteristics of the input data quality and the requirements on the outputs. Strategic Runway 

Configuration Management must be capable of operating with traffic demand and weather 

forecasts that include considerably more uncertainty than that which TRCM uses. Strategic 

Runway Configuration Management operates independently of both TRCM and CADRS due to 

the time horizons involved.

The algorithmic approach used for SRCM will compare aggregate demand and capacity, within 

the constraints imposed by weather and other external factors. In contrast, TRCM models 

individual flights. Consequently, SRCM may employ a more robust algorithmic approach, 

explicitly considering the possible outcomes due to the uncertainty in the input data.

The available weather forecasts in the near-term may limit the resolution with which SRCM may 

plan the configuration schedule. For example, if wind forecasts are only available at 15-minute 

intervals, then SRCM will have no information on which to base configuration change times 

other than at those intervals for which the wind is forecast. It is anticipated that higher time 

resolution in forecasts will be available in the future.

If stochastic weather and traffic demand forecasts are available, SRCM will use these. In 

addition to stochastic inputs, the SRCM outputs will be stochastic and then a method for 

converting to a deterministic capacity prediction will be provided to support TFM uses that are 

not ready to consider uncertainty information. 

SRCM Algorithm

The algorithm developed for the SRCM capability is less mature than that developed for TRCM. 

This is because of the uncertainties involved with longer term planning. The current version of 

the SRCM algorithm considers forecast demand and forecast weather, as well as known air 

traffic management constraints such as navigation aids that are out of service, and evaluates the 

predicted capacity for each possible airport configuration. This capability produces a forecast for 

the airport capacity (both arrival and departure) that is balanced to match the demand. Due to the 

time horizon over which SRCM must operate, SRCM must consider the uncertainty in the 

demand and weather forecasts.

The SRCM algorithm is a “queuing model” in that it applies airport capacity models and tracks 

the number of aircraft entering the arrival and departure queues and being served by the airport 

in 15-minute epochs. The algorithm does not model the continuous, four-dimensional movement 

of each aircraft. The current configuration is assumed to be known. 
SORM Concept of Operations

40

Combined Arrival/Departure Runway Scheduling (CADRS)

CADRS Overview

Significant research on planning how groups of flights should be managed through runway 

assignment and sequencing to use runways efficiently is ongoing at NASA, from both an 

airspace perspective and an airport surface perspective. Capabilities under CADRS are not 

envisioned as a competing system but rather a set of requirements for the integration of airborne 

and surface runway planning. The intent is to ensure runway usage optimizes efficiency from a 

broader perspective than just the arrivals, departures, or runway delays.

Combined Arrival/Departure Runway Scheduling is the SORM concept element that is intended 

to efficiently manage ground traffic, increasing throughput while meeting arrival and departure 

schedules. Runway assignment is a key output of CADRS. This capability balances local 

airport goals such as demand for runways and minimizing taxi distance with traffic flow 

management goals such as complying with imposed restrictions. It also applies automation to 

coordinate runway usage more effectively than can be done manually by controllers in today’s 

environment.

Combined Arrival/Departure Runway Scheduling is a concept to enable efficient tactical 

planning of runway operations for individual flights. This element is a key component of the 

overall SORM concept. However, numerous other past and current research initiatives have 

studied the problem of planning individual aircraft operations on runways. Therefore, the 

SORM NRA project only studied more novel aspects of the CADRS requirements, primarily 

how airborne planning (typically arrival) and surface planning (typically departure) may be 

integrated and how to expand the scope over which runway operations are optimized, from 

considering only runway-based metrics to considering the efficiency of flights along their full 

trajectories between transition fixes and parking gates.

The objective of CADRS is to both ensure separate arrival and departure schedulers produce 

coordinated schedules and enable communication of constraints and efficiencies so that the 

arrival and departure solutions are globally optimal. As such, CADRS is not necessarily a 

system itself, but rather a set of requirements on the runway schedulers that are included within 

the CADRS grouping. Combined Arrival/Departure Runway Scheduling assigns individual 

flights to runways and sequences (or schedules) flights on each runway to maximize the 

efficiency of the airport or metroplex, in a way that is resilient to uncertainty. As a result, an 

optimized schedule will be presented to the tower and TRACON controllers. Note that the 

schedule will be a recommendation to controllers and traffic flow managers.

Combined Arrival/Departure Runway Scheduling is a tactical tool, determining the runway 

assignments and sequence or schedule for individual flights over a time horizon of less than one 

hour. Tactical Runway Configuration Management provides tactical airport configuration 

planning over a time horizon slightly longer than the CADRS time horizon, while SRCM 

predicts airport capacity over a longer, strategic time scale.

The simplest approach for TRCM and CADRS interaction is for CADRS to use TRCM’s airport 

configuration schedule; no information is provided from CADRS to TRCM. In this way, TRCM 

and CADRS may operate together, and each may operate independently. Tactical Runway 

Configuration Management may plan the airport configuration without CADRS being 
SORM Concept of Operations

41

responsible for runway scheduling. Similarly, CADRS requires knowledge of the airport 

configuration to manage runway schedules, but the airport configurations may be planned 

manually as done in current operations rather than TRCM.

An important design question is whether CADRS is limited to solving the runway scheduling 

problem within the constraint of the airport configuration schedule specified by TRCM. Current 

operations allow for runway assignments that are exceptions to the stated runway configuration 

to improve efficiency or respond to un-common and real-time situations. To ensure the airport 

(or metroplex) operates as efficiently with CADRS as under current procedures, the CADRS 

algorithm will need to search for and allow some exceptions to the TRCM-selected policies.

CADRS Algorithm

Despite sharing the runways and other resources, automation that plans arrival runway 

operations (i.e., assigns runways to arrivals, sequences arrivals, and spaces consecutive arrivals) 

and automation that plans departure runway operations are expected to be separate systems for 

the foreseeable future. Therefore, CADRS can be described as adding an arbitrator between the 

departure planner that produces a runway schedule that is optimal from the perspective of the 

airport surface and the arrival planner that produces a runway schedule that is optimal from the 

terminal-area perspective. In addition, TFM produces schedule constraints that must be 

considered, although they should already have been considered by the individual arrival and 

departure planners. Three possible CADRS approaches are global optimization, arbitration, and 

allocation. 

The global optimization approach is to merge the separate arrival and departure planner

formulations for the runway scheduling problem into a single, combined formulation and solve 

the new, larger problem. This approach is essentially a “one time” arbitration between the 

individual systems, as cost function elements are assigned relative weights in the combined 

formulation. The merging could occur in the problem formulation or with a solution method that 

finds the solution that optimizes a weighted combination of the two separate problems.

A second algorithmic approach is to build an arbitrator that interacts with separate arrival and 

departure planners. The arbitrator would receive proposed runway plans from each planner and 

then send some information to one of the planners to provide a new schedule (and possibly some 

supporting information like a cost-sensitivity) that satisfies some constraints; the arbitrator 

repeats this process with the other planner and iterates until the separate, myopic arrival and 

departure solutions have converged or, at least, are compatible.

The third approach is to build an allocation system that interacts with separate arrival and 

departure planners. Allocation may be considered to be a sub-class of arbitration. An allocation 

system assigns the shared resources to the two separate planners so as to decouple those systems. 

Decoupled from one another, whatever independent solutions the two runway schedulers 

determine within the bounds specified by the allocation system will be compatible with each 

other. In this situation, the allocation would need to be for both the runways and flights. For 

example, all arrivals could be assigned to the airborne planner and all departures to the surface 

planner and then runways or runway capacities assigned to each planner for periods of time. 

Each approach has advantages and disadvantages. A primary weakness of the global 

optimization approach is that once merged, future changes to the arrival and departure planning 
SORM Concept of Operations

42

logic may require re-merging and, therefore, this approach reduces future flexibility. This 

drawback is somewhat reduced by merging at the solution rather than at the problem 

formulation, but this itself reduces the flexibility in merging the problems.

One disadvantage of the arbitration approach is that convergence is not likely to be guaranteed 

and, therefore, some executive would be required to make a final decision. In addition, the 

arbitration method could depend on details of the separate runway scheduling systems, again 

reducing future flexibility. The allocation method seems feasible when the runway plans are 

used to manage traffic, but controllers provide final de-confliction between flights. Trajectorybased application of this approach would be highly susceptible to uncertainty. In terms of 

performance, the global optimization approach would have the highest performance. Allocation 

is likely to be the lowest performance approach.

A variety of different arbitration techniques are feasible. For example, the “loosely coupled 

scheduler” approach employed by Multi-center Traffic Management Advisor (McTMA) 

motivates a “flight type” arbitrator approach. In McTMA, all flights are treated as 

interchangeable, and rate profiles are passed between schedulers responsible for different points 

through the metering geometry. The separate airborne and surface schedulers might pass 

schedules of slots back and forth. Each scheduler in McTMA calculates a schedule of flights,

but then converts that to a “rate profile” (basically an allocation of slots) that is passed to the next 

up-stream scheduler, which is free to assign any flights into those slots (not necessarily the same 

as the downstream scheduler had predicted). The surface would calculate a runway schedule and 

pass the “abstracted” arrival slots to the airborne scheduler, as well as any flight specific 

restrictions on arrivals. The arrival scheduler, in turn, would calculate a runway schedule using 

the received restrictions on arrival capacity and estimates of departure demand, and provide 

abstracted departure slots to the surface scheduler, as well as any flight-specific departure 

restrictions. The surface scheduler would re-calculate a runway schedule using the received 

departure capacity and estimates of arrival demand. Similar to McTMA, the solutions are 

expected to converge (and adjust as new information becomes available) through iteration.

As the number of different types of flights increases, the approach of abstracting them into slots 

rapidly breaks down since the availability of a flight of the correct aircraft type may be 

limited. Unfortunately, the runway schedulers will likely need to consider at least some flights 

as unique. For example, two Boeing 757 arrivals that will cross the same corner post and land on 

the same runway at a given airport may be equivalent from an airborne scheduling perspective. 

However, one of these flights may have an occupied arrival gate while the other is late and a 

priority for the flight operator. From the perspective of the surface scheduler, there is a clear 

preference for the order of these flights such that they may not be able to be treated as 

equivalent.

Factors that Affect Runway Assignment and Sequencing/Scheduling

This section lists and discusses the factors that affect the runway scheduling decision, which 

includes runway assignment, sequencing, and possibly specific scheduling of individual aircraft.
SORM Concept of Operations

43

Table 8. Factors that Affect Runway Usage

Factor Description

Wind

Runway assignment: Wind generally does not 

affect runway assignment.

Runway sequence: Wind may affect the sequence 

of two flights if they are merging from different 

directions such that the wind slows the ground 

speed of one aircraft while increasing the ground 

speed of the other aircraft.

Runway time (spacing): Wind can affect runway 

times for arrivals by increasing the average interaircraft spacing. When the aircraft on the final 

approach leg gain or lose ground speed relative to 

aircraft on the downwind or base legs, aircraft 

may exhibit increased compression or increasing 

spacing. Controller uncertainty about aircraft 

ground speed due to variability between aircraft 

requires additional “buffer” to ensure necessary 

separation is maintained. Wind gusts can have a 

similar effect.

Visibility and ceiling

Runway assignment: Based on weather 

minimums for different instrument approach 

procedures (IAPs), runway availability may be 

limited.

Runway sequence: N/A

Runway time (spacing): Ceiling and visibility 

dictates whether or not visual approach 

procedures may be used12, affecting the feasible 

arrival rate and, therefore, runway scheduling 

(i.e., times). All of the factors that affect 

arrival/departure rates affect runway times (but 

not necessarily sequence or runway assignments).

 

12 Weather minima required for the issuance of a visual approach is 1000’ ceiling and 3 miles visibility. In practice 

visual approaches are not used unless the ceiling and visibility is significantly in excess of the allowable minima.
SORM Concept of Operations

44

Factor Description

Airport configuration

Runway assignment: The runway configuration 

(i.e., the set of runways designated to be the 

primary runways to be used) affects runway 

assignment. 

The default runway assignment rules, which may 

be part of the airport configuration, affect runway 

assignment.

Runway sequence: N/A

Runway time (spacing): Established procedures 

affect the required spacing between flights.

Noise mitigation rules

Runway assignment: Noise mitigation rules affect 

runway assignment, such as precluding jet aircraft 

from certain runways during certain designated 

periods.

Runway sequence: N/A

Runway time (spacing): N/A

Traffic demand level

Runway assignment: When the number of 

arrivals and departures is low, aircraft will often 

be assigned to the runway with the shortest taxi 

time. When the demand is high, runway 

assignment will be based on direction of flight to 

avoid crossing flight paths. Automation to plan 

conflict-free airborne trajectories and precisely 

plan/control arrival time at the runways for 

departures have significant potential to increase 

the ability to use non-default runways to better 

balance runways and reduce taxi times.

Runway sequence: The runway sequence will 

typically be close to FCFS when demand is lower 

and may be optimized (non-FCFS) to maximize 

capacity when demand is high.

Runway time (spacing): Controllers will often 

expend additional effort to fully use runway 

capacity when demand is high.

Table 8. Factors that Affect Runway Usage Continued
SORM Concept of Operations

45

Table 8. Factors that Affect Runway Usage Continued

Factor Description

Aircraft type

Runway assignment: Aircraft type affects which runways are 

feasible of use; some runways may not have adequate length 

for some aircraft; some runways may not be available due to 

noise restrictions for jet aircraft.

Runway sequence: Aircraft type affects sequencing flights on 

a runway. Aircraft of similar weight category will be 

grouped, to the extent possible, to maximize runway capacity.

Runway time (spacing): The weight category of adjacent 

flights on a runway affects the necessary spacing between 

those flights; this is the case for not only a single runway but 

also closely spaced parallel runways and intersecting runways

Aircraft capabilities

Runway assignment: Aircraft capabilities, such as ILS or 

RNP level, affect which runways may be assigned.

Runway sequence: N/A

Runway time (spacing): Aircraft capability, such as the ability 

to self-separate from a leading aircraft, may affect spacing at 

the runway.

Arrival / departure fixes

Runway assignment: The direction from which arrivals 

approach the airport, or initial direction of flight for 

departures, affects runway assignment.

Runway sequence: The initial direction of flight for 

departures affects sequence for consecutive departing aircraft 

since less separation is required if divergent headings (15 deg) 

will be flown immediately after departure. 

Runway time (spacing): Spacing for consecutive departing 

aircraft cannot be reduced (as in the divergent heading case) if 

aircraft are flying the same lateral path and altitude separation 

cannot be applied. 

TFM restrictions

Runway assignment: N/A

Runway sequence: The presence of a TFM restriction, such as 

MIT on all departures to a destination airport, may affect 

sequencing to ensure consecutive flights subject to the 

restriction are sufficiently separated.

Runway time (spacing): The TFM restriction affects the 

spacing of flights on a runway and, possibly, on different 

runways. 
SORM Concept of Operations

46

Factor Description

Route

Runway assignment: N/A

Runway sequence: Flights on same route (air or surface) will 

remain in the same order. Flights that must merge may be reordered relative to their un-impeded order on the first common 

segment.

Runway time (Spacing): Spacing for consecutive departing 

aircraft cannot be reduced (as in the divergent heading case) if 

aircraft are flying the same lateral path and altitude separation 

cannot be applied.

Earliest time at runway

Runway assignment: When a flight enters the terminal area or 

is ready to taxi or may affect runway assignment. This 

requires known flying time between fix and each runway for 

arrivals and taxi time between gate and each runway for 

departures.

Runway sequence: When each flight will be ready to use a 

runway affects the runway sequence.

Runway time (spacing): N/A

Flying time between fix and each 

feasible runway

Runway assignment: The flying time (after takeoff) between 

each runway and the departure fix affects runway assignment 

for departures.

Runway sequence: N/A

Runway time (spacing): N/A

Taxi time between parking gate 

and each feasible runway

Runway assignment: The taxi time (after landing) between 

each runway and the parking gate can affect runway 

assignment for arrivals.

Runway sequence: N/A

Runway time (spacing): N/A

Ease with which flight may be 

delayed

Runway assignment: N/A

Runway sequence: How easily a flight may be delayed (e.g., 

measured in terms of a cost metric) may affect the runway 

sequence.

Runway time (spacing): N/A

Table 8. Factors that Affect Runway Usage Continued
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47

Information Requirements

This section discusses the information input to and output from SORM. As part of identifying 

the information exchange, the information providers and users of SORM information are 

defined. 

SORM Stakeholders

Table 9 lists the SORM stakeholders, the ATC positions or automation systems that are currently 

involved in making or acting on SORM decisions, or will be in the future, and describes the 

stakeholder’s role in interacting with the SORM decisions. The SORM information stakeholders 

—the positions or automation systems that will provide and/or receive information to/from 

SORM—and what information they receive or provide are described in the following 

subsections.

Table 9. System-Oriented Runway Management Stakeholders

Stakeholder RCM CADRS

ATCSCC TFM Specialist

Current: Uses airport 

configuration prediction to 

forecast airport arrival capacity, 

which is an input to TFM 

decisions.

Future: In addition to current 

use, will use planned airport 

configuration schedule to 

forecast airport departure 

capacity. 

RCM may output capacity 

forecast directly rather than 

configuration schedule; capacity 

forecast may be stochastic. 

Airport configuration will be 

planned in coordination with 

configurations at other 

airports/metroplexes and TFM 

decisions.

Current: None (i.e., in the current 

environment, does not use 

runway assignments or planned 

flight sequence/times on the 

runways).

Future: None (i.e., in the SORM 

/ NextGen environment, uses 

runway assignments or planned 

flight sequence/times on the 

runways).

ATCSCC Automation

Current: TFMS (formerly 

ETMS) requires airport arrival 

capacity estimates.

Future: TFMS will be required 

to support the future role 

described above for the 

ATCSCC Specialist 

Current: None

Future: None
SORM Concept of Operations

48

Stakeholder RCM CADRS

ARTCC TMC

Current: Uses airport 

configuration prediction to 

forecast airport arrival capacity, 

which is an input to regional 

TFM decisions. Shorter time 

horizon than ATCSCC 

Specialist.

Future: No change as current. 

May also consider departure 

capacity when selecting 

departure TMIs.

Current: Initiates formal “delay” 

procedures including “ground 

stops” and assignment of 

departure release times for 

individual flights EDCTs.

Future: ASDO/CADRS 

departure release times will 

comply with TFM restriction, 

which will continue to be 

manually selected by the TMC.

Necessary TMIs will be 

incorporated into 4D trajectories 

such that the TMC will no longer 

need to manually apply TFM 

restrictions on individual flights.

ARTCC TMU Automation

Current: TFMS requires 

configuration to predict capacity 

and flying times within the 

terminal airspace.

Configuration changes can also 

require automation changes and 

affect Standard Terminal Arrival 

Route assignments in adjacent 

ARTCCs.

Future: Handle stochastic 

capacity forecasts.

Current: Uses current automation 

to help make TFM decisions that 

affect runway schedule; TMA 

used to meter arrivals.

Future: Automation such as 

TMA/TBFM or DFM may select 

departure release times 

automatically.

TFMS could use departure 

schedule to improve sector entry 

time predictions.

ARTCC Area Supervisor

Current: Uses planned 

configuration changes for 

staffing decisions.

Future: Same.

Current: None

Future: None

Table 9. System-Oriented Runway Management Stakeholders Continued
SORM Concept of Operations

49

Table 9. System-Oriented Runway Management Stakeholders Continued

Stakeholder RCM CADRS

ARTCC Sector Controller

Current: En route automation 

modernization (ERAM, 

formerly Host) requires 

configuration to configure 

controller’s scopes and process 

flight plans properly.

Configuration may be required 

to plan arrival aircraft altitude to 

enter TRACON at correct 

altitude (“short” side vs. “long” 

side).

Need to know last arrival prior 

to a configuration change to plan 

delay absorption strategy.

Future: Same

Current: None

Future: None

TRACON TMC

Current: None

Future: RCM would be 

available for TMC.

Current: None

Future: ASDO would plan 

arrival runway assignments and 

sequence/schedule.

TRACON Supervisor

Current: Use configuration 

changes to make staffing 

decisions.

Future: Same

Current: None

Future: None

TRACON Arrival Controller

Current: Configuration used to 

manually make runway 

assignments and other ATC 

decisions.

Need to know the last arrival for 

the prior configuration from 

each fix.

Future: More frequent 

configuration changes may 

require CADRS to maintain 

acceptable workload.

Current: Manually make 

runway assignment and 

sequence decisions.

Future: CADRS provides 

runway assignment and 

sequence/schedule.
SORM Concept of Operations

50

Stakeholder RCM CADRS

TRACON Arrival Controller’s 

Automation

Current: Standard Terminal 

Automation Replacement 

System (STARS) and 

Automated Radar Terminal 

System (ARTS) require airport 

configuration to configure 

controller’s displays properly.

Future: Same

Current: Runway assignment 

manually entered.

Future: Runway assignment 

received from CADRS. 

Sequence/schedule at runway or 

merge points may be received 

from CADRS.

TRACON Departure Controller

Current: Uses knowledge of 

configuration to configure 

automation and know what to 

expect.

Future: CADRS will provide 

advanced knowledge of 

departures; configuration may 

not be required.

Current: No responsibility for 

runway assignment or 

scheduling. Uses some 

information about departure 

sequence for planning.

Future: Will use CADRS 

departure runway assignment 

and sequence/schedule for 

planning.

TRACON Departure 

Controller’s Automation

Current: STARS and ARTS 

require airport configuration to 

configure controller’s scopes 

properly.

Future: Same

Current: None

Future: CADRS departure list 

will be available through 

STARS/ARTS.

ATCT TMC

Current: Makes or is involved in 

selecting the airport 

configuration.

Future: Same as current.

Current: May manually 

recommend runway assignments 

or sequences.

Future: When CADRS is being 

used, no role.

ATCT TMC’s Automation

Current: Automation, such as 

TMA, is used to visualize traffic 

demand; weather data is 

obtained from various sources.

Future: TFDM will provide the 

RCM-planned configuration 

schedule.

Current: Paper flight strips are 

used to visualize demand for 

various resources from which 

suggestions for exceptions from 

default rules are made to 

improve efficiency.

Future: SESO/CADRS will 

provide runway assignments and 

sequences/schedules for 

departures.

Table 9. System-Oriented Runway Management Stakeholders Continued
SORM Concept of Operations

51

Table 9. System-Oriented Runway Management Stakeholders Continued

Stakeholder RCM CADRS

ATCT Supervisor / Controllerin-Charge (CIC)

Current: Uses planned 

configuration change times for 

staffing decisions and to respond 

to airport authority maintenance 

requests.

Future: Same as current.

Current: None

Future: None

ATCT ATC Coordinator 

(coordinates between 

control/non-control positions 

in the tower)

Current: Same as local and 

ground controllers.

Future: Same as local and ground 

controllers.

Current: Same as local and 

ground controllers.

Future: Same as local and ground 

controllers.

ATCT Clearance Delivery / 

Flight Data Controller

Current: Uses airport 

configuration to verify flight plan 

validity.

Future: Same as current 

operations. Access RCM-planned 

configuration from TFDM. More 

frequent configuration changes 

may require automation to assist.

Current: None

Future: Issue expected runway 

assignment or taxi route from 

SESO/CADRS.

ATCT Ground Controller

Current: Uses airport 

configuration to assign departure 

runways and sequence aircraft as 

well as assign taxi routes.

Uses planned configuration 

changes to plan runway 

assignments and taxi routes.

Uses configuration to assign 

arrival taxi routes.

Future: Configuration will not be 

required; CADRS will provide 

runway assignments and SESO 

will provide taxi route decisions.

Current: Manually assigns 

departure runways and sequence.

Future: CADRS selects departure 

runway and sequence.
SORM Concept of Operations

52

Stakeholder RCM CADRS

ATCT Local Controller

Current: Uses knowledge of 

airport configuration (including 

procedures) to apply separation 

between departures on a runway 

and between operations on 

interacting runways.

Uses airport configuration to 

select taxi route for arrival 

aircraft.

Future: CADRS provides 

sequence; configuration will be 

required for controller(s) to apply 

correct separation. 

CADRS makes runway schedule 

decisions; controller no longer 

needs to know configuration for 

aircraft separation.

Current: Select departure 

sequence; selects when to taxi 

aircraft across active runways.

Future: CADRS may specify 

sequence; controller must apply 

separation manually. When 

CADRS provides schedule and 

runway crossings, controller no 

longer needs to make these 

decisions. CADRS output 

provided via TFDM.

ATCT Controller Automation

Current: ATIS updated with new 

configuration.

Enhanced Status Information 

System or a similar system used 

to display current configuration. 

Manual entries to change 

configuration. 

Future: TFDM will host SESO 

and CADRS.

Current: Paper flight strips. 

Departure Spacing Program or 

bar-coded flight strips in a few 

airports.

Future: SESO and CADRS via 

TFDM.

Flight Operator’s Ramp Tower 

/ Station

Current: At airports where the 

taxi direction from the gate 

depends on the assigned runway, 

uses airport configuration to 

determine direction to taxi in the 

ramp.

Future: Taxi route provided to 

Flight Operator such that 

configuration is not required.

Current: None

Future: CADRS runway 

assignment and sequence used to 

predict ON and OFF times; 

SESO predicts IN times and 

controls OUT or spot times; 

improved predictability for 

operator.

Table 9. System-Oriented Runway Management Stakeholders Continued
SORM Concept of Operations

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Table 9. System-Oriented Runway Management Stakeholders Continued

Stakeholder RCM CADRS

Flight Operator’s (AOC)

Current: Use configuration for 

general planning and expected 

airport delays. Get 

configuration from staff on-site 

at airport or predictions based 

on weather forecasts.

Future: Receive planned 

configuration schedule from 

RCM. Provide preferences for 

the airport configuration.

Current: None

Future: Improved predictability 

for flight operator.

Airport Authority

Current: Use configuration to 

plan snow removal and 

maintenance. Observe 

configuration or call ATCT for 

configuration.

Future: Receive planned 

configuration schedule from 

RCM. Participate in planning 

process as appropriate when 

there is discretion regarding the 

use of resources, e.g. anticipated 

maintenance.

Current: None

Future: None

Strategic Runway Configuration Management

Information Required by SRCM

SRCM will require forecasts for each of the required input data over a time horizon at least as 

long as SRCM computes outputs. SRCM inputs may be grouped into three types: traffic 

demand, weather, and airport information. Traffic demand data describes the following:

 Flights that are expected to use the airport, including status as an arrival or departure 

 When the flight plans to use the airport 

 The flight’s route of flight or direction of flight relative to the airport 

 The aircraft type

All of this information affects the airport resources required to serve the flight. The traffic 

demand data will likely be provided by TFMS. The data is required at least as frequently as 

SRCM will run to produce updated outputs. Weather data consists of the elements of weather 

considered by SRCM to determine the airport configuration. Weather may include wind speed 

and direction, ceiling and visibility, and precipitation at the airport, as well as runway visual 

range, terminal area winds, and convective weather in the terminal area that would block routes. 
SORM Concept of Operations

54

The lack of availability of weather forecasts for certain weather elements may delay SRCM from 

including those elements until new information becomes available. The update rate of weather 

forecasts may be less frequent than SRCM re-computes outputs. However, the traffic demand 

input data will be updated more frequently than required.

Airport information includes the description of the defined airport configurations and the weather 

and other conditions under which each configuration may be used. This data is generally static 

for many days, with occasional changes resulting from construction or procedure changes, for 

example. This data is expected to be manually generated as part of adapting SRCM to an airport 

or metroplex.

Information Provided by SRCM

SRCM will provide a forecast of airport capacity as a function of time for the time period 

beginning at the present time and extending six hours into the future. The forecast will specify 

the maximum arrival capacity for each quarter hour. SRCM will provide a new forecast every 

15 minutes, on the quarter-hour. In addition, SRCM will provide forecasts of departure capacity 

and airport configuration. The forecast arrival and departure capacities consider the demand at 

the airport and required tradeoff associated with allocating resources to either arrivals or 

departures. The configuration will allow the information recipient to consider alternative 

tradeoffs that may provide a higher or lower arrival capacity. The SRCM forecasts may be 

stochastic, presenting the uncertainty known to exist due to uncertainty in input data and control 

decisions external to SRCM. 

Entities that Interact with SRCM

Table 10 summarizes the stakeholders for the SRCM functionality and what information they 

either provide to or receive from SRCM.

Table 10. Strategic Runway Configuration Management Stakeholders and Information 

Exchanged

Stakeholder Information Received or Provided

ATCSCC Specialist

ARTCC TMC

Receives airport configuration and capacity forecast for use in 

TFM decisions.

TFM Automation

Receives airport configuration and capacity forecast for use in 

forecasting traffic situation and advising TMIs.

Provides forecast traffic demand.

Flight Operator’s Airline 

Operations Center 

Receives airport configuration and capacity forecast for 

planning resources.

Provides configuration preference.
SORM Concept of Operations

55

Stakeholder Information Received or Provided

Airport Operator

Receives airport configuration and capacity forecast for 

planning resources.

Provides plans for use of airport resources.

Weather Automation Provides weather forecast.

Tactical Runway Configuration Management

Information Required by TRCM

TRCM requires the same basic information as SRCM—weather forecast, traffic demand 

forecast, and airport (or metroplex) information— over a shorter time horizon. In addition to 

receiving traffic demand data from TFMS, more accurate arrival time predictions may be 

received from TMA. If insufficient weather data is available from other systems, then the 

system hosting TRCM functionality may allow for manual entries such as whether or not the 

runways are wet.

Information Provided by TRCM

Tactical Runway Configuration Management will provide a schedule of planned airport 

configurations over the next hour. The information associated with each planned change may 

include identification of the last aircraft for the prior configuration. 

Entities that Interact with TRCM

Table 11 summarizes the stakeholders for the TRCM functionality and what information they 

either provide to or receive from TRCM.

Table 11. Tactical Runway Configuration Management Stakeholders and Information 

Exchanged

Stakeholder Information Received or Provided

TRACON TMC

TRACON Supervisor

ATCT TMC

ATCT Supervisor / CIC

Receives planned airport configurations (over next hour) for 

implementing and making local traffic management decisions.

Table 10. Strategic Runway Configuration Management Stakeholders and Information 

Exchanged Continued
SORM Concept of Operations

56

Stakeholder Information Received or Provided

TRACON Arrival Controller

TRACON Departure Controller

ATCT Ground Controller

ATCT Local Controller

ATCT Flight Data / Clearance 

Delivery positions

Receives current and planned airport configuration changes 

(over next 15–30 minutes) to control aircraft.

TFM Automation Provides forecast traffic demand.

Flight Operator’s Airline 

Operations Center 

Receives airport configuration and capacity forecast for 

planning resources.

Provides configuration preference.

Airport Operator

Receives airport configuration and capacity forecast for 

planning resources.

Provides plans for use of airport resources.

Weather Automation Provides weather forecast.

Combined Arrival Departure Runway Scheduling

Information Required by CADRS

Combined Arrival Departure Runway Scheduling will receive information from terminal area 

arrival management and airport surface departure management automation systems. Details on 

this information exchange will be identified as the CADRS concept and algorithm are studied 

further.

Information Provided by CADRS

Combined Arrival Departure Runway Scheduling provides a coordinated plan for how arrivals 

and departures will use the runways: runway assignments and either sequence (near-term) or 

schedule (under 4D trajectory-based operations). This runway plan will initially cover the next 

30 minutes and eventually the next 60 minutes. The runway plan for the next few minutes may 

be updated every few seconds based on new surveillance data indicating compliance deviations 

from the prior plan. The plan for times further from the current time may be updated less 

frequently.

Table 11. Tactical Runway Configuration Management Stakeholders and Information 

Exchanged Continued
SORM Concept of Operations

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Entities that Interact with CADRS

Table 12 summarizes the stakeholders for the CADRS functionality and what information they 

either provide to or receive from CADRS.

Table 12. Combined Arrival Departure Runway Scheduling Stakeholders and Information 

Exchanged

Stakeholder Information Received or Provided

TRACON Arrival Controller

TRACON Departure Controller

ATCT Ground Controller

ATCT Local Controller

ATCT Flight Data / Clearance 

Delivery Controller positions

Receives runway assignments and sequence/schedule

ASDO Automation

SESO Automation

Provides runway assignments and sequence/schedule.
SORM Concept of Operations

58

SORM Research and Development Status

This section briefly summarizes the current status of SORM development. 

Runway management research under the SORM effort has been ongoing over the past five years. 

Much of the work described in this document has focused on the development of SORM over the 

initial three years. For that period, research was conducted as three one-year spirals to develop 

basic capabilities for a single airport in the first year, more complex SORM capabilities for a 

single airport in the second year, and SORM capabilities for a metroplex environment in the third 

year. The first year of SORM research focused on concept engineering, such as identifying 

SORM-use cases and information requirements for potential SORM users. Initial algorithm 

exploration was also conducted in addition to preliminary investigation of SRCM. The second 

year of SORM research saw the development and testing of TRCM and CADRS prototypes 

applicable to a single airport as well as continued work on SRCM. The third year of SORM 

research focused on developing a prototype of TRCM that is applicable to metroplex 

environments.

This research program has proven laboratory prototypes for some elements of the SORM 

concept. Additional research is required to develop field prototypes including user interfaces, to 

conduct field tests of the technology, to address issues necessary to ensure compatibility with

FAA systems, and to ensure the full variety of airport and metroplex characteristics are handled. 

In addition, further research on less-studied aspects of the SORM concept is needed.

Two types of software have been developed during SORM research and development. Initial 

work to evaluate concepts and design algorithms has been performed in Matlab, to take 

advantage of the flexibility and integration of software development and analysis. Subsequently, 

SORM algorithms selected for further study have been coded in Java. The Java software 

development consists of implementing SORM algorithms and enhancing the Metroplex 

Simulation Environment (MSE).

The MSE is used as a platform for the SORM software, providing the necessary input data, such 

as weather and traffic forecasts and static adaptation data describing the airport and defined 

airport configurations. The MSE is also used to run fast-time simulations, either implementing 

the airport configurations suggested by SORM or using scripted baseline airport configurations 

obtained from historical data. The simulations produce a variety of metrics which are then used 

to measure the performance of SORM relative to the baseline simulation. Figure 3 provides a 

high-level architecture of the implementation of the TRCM algorithm within MSE.

A user interface was developed in the course of the SORM research effort that is conceptual in 

nature. The philosophy underlying the design reflects the FAA’s move toward fewer displays in 

the tower and the ready availability of the pertinent information required by air traffic personnel 

to make runway management decisions. A description and depiction of the interface can be 

found in Appendix A. 

Analysis work has been conducted in the past year to assess benefits of the TRCM capability. 

The work focused on capacity, efficiency, and impact on delay. The publications are in the final 

review process (refs. 20 and 21).
SORM Concept of Operations

59

Figure 3. Tactical Runway Configuration Management in MSE.

Over the course of the SORM research and development, several airports have been used for 

SORM testing. John F. Kennedy International Airport was selected as the focus airport for 

single-airport SORM testing. However, for a variety of reasons related to the complexity of 

operations in the New York metroplex, KJFK does not make many airport configuration 

decisions; the TRACON usually makes these decision. To study the importance of dimensions of 

airport configuration in addition to runway configuration, the application of SORM was also 

studied at KMEM, KMCO, and KATL. Studying four different airports ensured the system 

design is flexible and the concept is readily adaptable to different airports, which each possess 

unique characteristics.

The application of SORM to a metroplex environment was tested in the context of the New York

metroplex, which was defined as consisting of primarily KJFK, KLGA, Newark Liberty 

International Airport, and Teterboro Airport. 
SORM Concept of Operations

60

Summary

Significant inefficiencies exist at airports throughout the NAS with respect to arrival and 

departure operations. The effective management of runways is central to addressing these 

inefficiencies. The airport runway sits at the crossroads of the airport surface and the airspace 

environment. Although technically part of the airport surface, the runway and management of 

this resource can be thought of as a process separate from other surface automation capabilities. 

The two capabilities, surface and runway management would ultimately have to be coordinated, 

however. This document defines a concept, System-Oriented Runway Management that 

addresses effective runway management through the determination of optimal runway 

configurations and subsequent runway assignment policies. The development of SORM 

capabilities assumes that consideration of the broader landscape of operational factors on the 

airport surface and in the airspace is required for effective and viable solutions. Further, SORM 

was developed with the understanding that any effective runway management capability must be 

complementary to the broader challenge of Airport Configuration Management. In addition to 

the airport and related surface operations, the effects of runway configurations/usage are crosscutting in terms of their effect on other elements/ processes of the air traffic system. Airspace 

operations, TFM, and airline operations, among others, are all affected by runway management 

decisions. This effect will be amplified for concepts and technologies under investigation for the 

future. Dynamic reconfiguration of the airspace, potential changes in wake separation standards, 

and migration to a fixed-path environment coupled with the use of required times of arrival are 

but a few examples.

System-Oriented Runway Management is composed of three elements: Strategic Runway 

Configuration Management, Tactical Runway Configuration Management, and Combined 

Arrival Departure Scheduling. Strategic Runway Configuration Management forecasts the 

airport configuration over a longer time horizon for the purpose of providing airport capacity 

forecasts for use in traffic flow management—planning TMIs several hours in advance. Tactical 

Runway Configuration Management plans the airport configuration over a timeframe appropriate 

for air traffic personnel in the ATCT and TRACON to make runway configuration and operating 

procedure decisions used to control arrival and departure traffic. Combined Arrival/Departure 

Runway Scheduling is more tactical in nature than TRCM; it plans how individual flights should 

use the available runways and is subject to (or in exception to) the aggregate policies selected by 

TRCM. 

Algorithms have been developed that address each of the three SORM capabilities. Emphasis 

has been placed on algorithm development for TRCM addressing both the single airport and 

metroplex environments, with the former currently at a higher level of maturity. Single airport 

TRCM considers overall delay (not just delay at the runway), costs due to reduced capacity 

during this period, among other factors. Compute power to run the algorithms are well within 

capabilities that exist today. Future envisioned capabilities for the TRCM will incorporate inputs 

from system users and airport operators. For metroplex TRCM, algorithms will be further 

developed to incorporate the dependencies between flight paths as well as airspace. Capabilities 

that address prioritization of resources will be an integral part of future functionalities; e.g.,

priority of operations at one airport over another may be required in the interest of NAS 

performance. This may drive runway configuration selection.
SORM Concept of Operations

61

In support of the SORM research effort four airports (for the single runway cases) have been 

modeled: KJFK, KMEM, KMCO and KATL. Limited simulation and evaluation of SORM tools 

in these environments has been conducted and positive results have been observed in all cases. 

Note that with runway configuration management tools, trade-offs are an inherent part of the 

selection process so there will be negative benefit value in some cases; however it is the overall 

benefit that is the focus of runway management optimization. For the multiple airport case, the 

New York Metroplex was modeled, the four major airports- KJFK, KLGA, KEWR, and 

Teterboro. Extensive benefits analysis for both of the single airport and the metroplex 

capabilities have recently been completed and will be published in the near future.

The single airport TRCM was transferred to the FAA in April, 2012 through a technology 

transfer agreement; the multiple airport version of TRCM will be transferred in March 2015. 

Further development of both SRCM and CADRS capabilities are planned. Plans are in place for 

integration of SORM capabilities with other work areas within NASA’s Airspace Systems 

Program. There is also a collaboration agreement between NASA and the German Aerospace 

Center (DLR) focused on the integration of DLRs arrival/departure and surface capabilities and 

the TRCM algorithm. The collaboration agreement has been in place for one year, and a proposal 

is under consideration that would extend the work for two additional years.
SORM Concept of Operations

62

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R&D Seminar, Budapest, Hungary, 2003.

19. Glass, B, “Automated Data Exchange and Fusion for Airport Surface Traffic 

Management,” AIAA Paper 97-3679, 1997.

20. Phojanamongkolkij, N., R. Oseguera-Lohr, G. Lohr, S. Robbins, and J. Fenbert, “Benefit 

Assessment for Metroplex Tactical Runway Configuration Management,” NASA 

TM/0000-000000 (in publication), 2014 

21. Oseguera-Lohr, R., G. Lohr, N. Phojanamongkolkij, “Benefits Assessment for Tactical 

Runway Configuration Management Tool,” NASA TM/0000-000000 (in publication), 

2014.

22. Jones, Debra, M. Lenox, and E. Onal, (2012). System-oriented runway management 

(SORM) decision support tools and user interface support. Internal report to Stinger 

Ghaffarian Technologies, element 5.2, deliverable #2; under NASA LITES Task A099. 

Guide to Further Reading

23. Provan, Chris, “Optimization Models for Strategic Runway Configuration Management,” 

10th AIAA Aviation Technology, Integration, and Operations (ATIO) Conference, Fort 

Worth, TX, 13–15 September, 2010.

24. Weld, C., M. Duarte, R. Kincaid, “A Runway Configuration Management (RCM) Model 

with Marginally Decreasing Transition Capacities,” 2010 IEEE Systems and Information 

Engineering Design Symposium (SIEDS), Charlottesville, VA, 23 April, 2010.

25. Kincaid, R., R. Zhang, M. Haines, and J. Thorne, “Optimization Models for Runway 

Configuration Management,” 12th INFORMS Computing Society Conference, Monterey, 

CA, 9–11 January 2011.

26. Provan, C. and S. Atkins, “Tactical Airport Configuration Management,” IEEE/AIAA 

Integrated Communications Navigation and Surveillance (ICNS) Conference, Herndon, 

VA, 10–12 May 2011.

27. Lohr, G., S. Brown, H. P. Stough, S. Eisenhawer, S. Atkins, and D. Long, “System 

Oriented Runway Management: A Research Update,” USA/Europe Air Traffic 

Management Research and Development Seminar, Berlin, Germany, 14–17 June 2011.

28. Lohr, G., S. Brown, S. Atkins, S. Eisenhawer, T. Bott, D. Long, S. Hasan, “Progress 

Toward Future Runway Management,” 11th AIAA-ATIO Conference, Virginia Beach, 

VA, 20–22 September 2011.
SORM Concept of Operations

64

29. Zhang R. and R. Kincaid, “Robust Optimization for Runway Configuration 

Management,” 11th AIAA-ATIO Conference, Virginia Beach, VA, 20–22 September 

2011.

30. Thorne J. and R. Kincaid, “Tabu Search for Tactical Runway Configuration 

Management,”12th AIAA-ATIO Conference, Indianapolis, IN, 17–19 September 2012.
SORM Concept of Operations

65

Examples of Airport Geometries

This appendix is composed of eight airport diagrams. The diagrams in Figure A-1 – Figure A-8

are intended to illustrate differing airport surface geometries. Coupled with these differences are 

the unique procedural requirements that are inevitably part of different local operational 

environments.

Figure A-1. Los Angeles 

International Airport.

Figure A-2. John F. 

Kennedy International 

Airport.

Figure A-3. San Francisco 

International Airport. 

Figure A-4. Ronald Reagan 

Washington International Airport.

Figure A-5. General Edward 

Lawrence International Airport.
SORM Concept of Operations

66

Figure A-6. San Diego 

International Airport. 

Figure A-7. Philadelphia 

International Airport.

Figure A-8. Dallas-Fort 

Worth International 

Airport.
SORM Concept of Operations

67

Descriptions of Decision Making process for 

Runway Configuration Selection at Two Select Airports

This appendix provides an overview of the decision-making process with respect to runway 

management for two large airports: Dallas-Fort Worth International Airport (KDFW) and 

Memphis International Airport (KMEM). Note that there are common considerations such as 

those identified in sub-section 2.2.1; a few of the more common considerations include the 

following:

 Wind direction and speed

 Convective weather activity in the TRACON airspace: if thunderstorms would affect 

traffic flow on the final approach courses for one configuration, but not affect the 

final approach courses for another runway configuration

 Equipment outages, for example components of the Instrument Landing System 

(ILS), e.g., the glide slope or localizer

 Runway or taxiway closures

 Procedures affecting the departure capacity 

 Configuration changes which must be negotiated at high density TRACONs with 

several busy airports. Wind forecasts are critical in these instances. 

 Noise abatement procedures—certain configurations are required during “quiet time” 

operations 

B.1. Dallas-Fort Worth International Airport Example

At KDFW, the TRACON TMU selects the configuration change time and the ATCT typically 

accepts the recommendation. A TRACON TMC looks at the forecast weather, primarily wind 

direction and speed, and at the arrival demand using the traffic management advisor (TMA). 

The TMC wants to set the change time at least 20 minutes in advance, 40 minutes is preferred, 

with a possible refinement of the time at 30 minutes in advance.

The TMC chooses the last arrival across each arrival fix, using the TMA estimated time of 

arrival at the fix and runway. They look for coincident gaps (adjusted for flying time to the 

runway) between arrivals at each of the arrival fixes. All arrivals after the designated last flight 

for each fix go into holding. The change time represents the time the airport surface changes 

configurations, which effectively is the time the last of the arrivals for the old configuration 

lands.

All departures in the old configuration must be airborne three minutes before the change time. 

This same requirement applies to both Dallas Love Field and KDFW. Sometimes, the TRACON 

TMU will require the last departure to be airborne five minutes prior to the change time. 

Departures may resume in the new configuration immediately after the change time.

Arrivals from the “long flight time” side can resume for the new configuration five minutes 

before the change time. Arrivals from the short side can resume three minutes before the change 

time. The goal is for the last four arrivals in the old configuration to land just before the change 
SORM Concept of Operations

68

time. These flights cross the arrival fixes about 15 minutes before the change time. Therefore, 

there is about a 10- minute period when no arrivals are crossing the arrival fixes and, 

equivalently, for the first 10 minutes in the new configuration there are no arrivals landing on the 

runways.

If a change is required during a busy traffic period, the TRACON TMU may stop all traffic to 

and from the satellite airports during the entire period the airport and airspace are flushing the 

traffic in the old configuration and establishing the new flows to reduce traffic complexity.

Planning a configuration change involves not only selecting a time at which the airport surface 

switches configurations but times at which arrivals and departures stop for the old configuration 

and start for the new configuration and, further, identifying the last/first aircraft. Dallas-Fort 

Worth currently uses rules-of-thumb that experience has shown avoids airborne conflicts. 

B.2. Memphis International Airport Example

The current winds dictate the runway configuration most of the time. The FAA Order 7110.65, 

section 3-5-1 requires the use of the runway most nearly aligned with the wind when five knots 

or more, and the “calm wind” runway when less than five knots. The calm wind runway is 

specified in the local Standard Operating Procedures; not all airports have specified a calm wind 

runway or configuration. When the wind is calm, or nearly calm, other factors are considered. 

At KMEM the tower cab supervisor or CIC determines the configuration. Normally, the CIC

will select the configuration that results in the highest airport acceptance rate. 

At KMEM, for instance, runway 27 crossover procedures make it desirable to not use runway 27 

frequently if the departure volume is mostly FedEx. At Newark International Airport, if a ship is 

docked at a particular pier, their most popular airport configuration is unavailable until that ship 

departs, because its height conflicts with the missed approach procedure for that runway.

Another consideration is arrivals versus departures and their taxi distance. Passenger aircraft are 

based roughly in the middle of the airport. Since taxi distance is not a critical factor for them,

they rarely comment on, or request a particular configuration. FedEx, on the other hand, is very 

interested in configuration because of their ramp location. FedEx’s operations personnel 

frequently call the Memphis TRACON to request a particular configuration at KMEM.

For operations at night, the configuration is decided in a conference call with Memphis CenterTMU, the TRACON, and the tower. The terminal forecast is used. The TMU supervisor also 

discusses the forecast with the center’s meteorologist prior to conferencing with the tower or 

FedEx. These conferences are held about four hours prior to the start of the FedEx 

arrivals. FedEx needs this information well in advance for fueling considerations and planning 

arrival parking gates. However, the situation can, and often does, change at the last minute.

At KMEM, FedEx prefers to land to the north and depart to the south to minimize taxi distance. 

The KMEM airport layout is shown in Figure B-1. However, FedEx has discovered that if they 

land with a tailwind component up to 10 knots, more of their planes get on the ground faster and 

the resulting savings outweighs those resulting from shorter taxi times to the parking gates. 

Analysis of actual operations has revealed that the aircraft on final approach have less interarrival spacing, and groundspeeds are higher with a modest tailwind. This is an example of the 
SORM Concept of Operations

69

importance of considering the effect of runway configuration on both airborne trajectories and 

surface trajectories and selecting the option with the highest overall efficiency.

Figure B-1. Memphis International Airport.

In normal daytime operations, if the supervisor foresees a configuration change, he/she will 

decide to execute the change in time to have the aircraft positioned correctly when the actual 

change takes place; this is usually no more than 20 minutes in advance.

The terminal weather forecast from the National Weather Service is used for longer term 

planning. It is issued every six hours. Observing wind reports from stations close to the airport

to the west, like West Memphis, Jonesboro, or Walnut Ridge, gives the supervisor an idea of 

what the trend is and when he/she can expect to see a change. These are usually updated 

hourly. The Integrated Terminal Weather Service (ITWS) weather system is also valuable, since 

it shows gust fronts and wind data near the outer fixes; ITWS is continuously updated. The 

tower supervisor may also use visual cues in determining wind changes. At KMEM, they will 

often check the direction smoke is blowing from smoke stacks west of the airport, as an indicator 

of a change in wind direction or magnitude. 

Traffic demand information is primarily based on historical knowledge and experience rather 

than any data source. The traffic patterns at KMEM and most airports are regular and 

predictable. Traffic Flow Management System /Traffic Situation Display and flight strips may 

be used if traffic is not expected to be similar to most days.

When the configuration will be changed, the tower supervisor/CIC calls the TRACON 

supervisor and advises of the new configuration and change time. The TRACON supervisor 
SORM Concept of Operations

70

advises the arrival and departure controllers of the plan for the configuration change. 

Communicating a configuration change also requires recording a new Automatic Terminal 

Information System (ATIS) broadcast13 and calling the overlying ARTCC TMU. The TMU will 

then enter the change in the National Traffic Management Log (NTML), unless the TRACON 

has TMU and NTML access. The center TMU will also inform its operational sectors that 

require the information, either by phone, the Enhanced Status Information System (ESIS), 

general information (GI) message, or hand-held radio. Depending upon their working 

relationship, the TRACON or TMU supervisor may call one or more major users either during 

the decision-making process, or to inform them when the decision has been made. 

The ESIS display is a function of the NTML. When a restriction comes through the NTML, the 

receiver can edit it and display it on a screen so that it is available to everyone. At ZME there is 

an ESIS display in the TMU and in each of the six operational areas. The display has different 

sections that show restrictions, airport information, and military activity. The ESIS display will 

automatically update information (e.g., if times or altitudes change) based on changes in NTML. 

Restrictions change color close to the expiration time and then disappear after expiration. Not 

every facility uses ESIS, and some use it differently, but it has become the primary source for 

current restrictions in the center.

A GI message is the old way of disseminating information at a center. This is entered into an en 

route automation modernization terminal and prints out on the flight strip printer at each 

sector. This method is still used to issue some operational information and a lot of nonoperational information in the center.

At KMEM, specified procedures like those described for KDFW to identify when the last 

arrivals/departures in the old configuration must be across the fix/airborne and when the 

arrivals/departures for the new configuration may cross the fix/take off do not exist. For arrivals, 

the TRACON supervisor will advise the tower which arrival will be the last one for the old 

configuration. For departures, the tower supervisor will advise the TRACON supervisor which 

departure will be the last one for the old configuration. The supervisors will always coordinate 

with the controllers before making the decision.

In addition to the runways in use, the configuration must specify some procedures such as 

whether IAPs or visual approaches may be used. A visual approach cannot be issued if the 

reported weather at the airport is at or below basic visual meteorological conditions minima 

(1000’ cloud ceiling and 3 miles visibility). Note that in practice, visual approaches are not used 

unless the weather is significantly better than the required minima. Visual approaches are, 

however, used whenever possible, but must also be accepted by the pilot.

 

13 Clearance delivery or the flight data position is responsible for the ATIS broadcast. At many locations, the ATIS 

is now digitized and the controller simply selects the information to include.
SORM Concept of Operations

71

An Airport Runway Management User Interface 

and Decision Support Toolset

To achieve the objectives of this project, SA Technologies, Inc. utilized the innovative Situation 

Awareness-Oriented Design (SAOD) approach. The SAOD process is a user-centered approach 

that covers all aspects of system design from requirements analysis, to design development, to 

evaluation of the resultant designs. This approach has been effectively utilized and validated 

across a variety of domains and results in validated, user-accepted graphical user interface (GUI) 

designs. SAOD is comprised of three main stages: requirements analysis, GUI design, and 

measurement (Figure C-1).

Figure C-1. SAOD Process.

The first phase of the SAOD process focused on understanding requirements, both from a user 

perspective and from a technology perspective. To understand the users’ requirements, SAOD 

utilizes a form of cognitive task analysis called a Goal-Directed Task Analysis (GDTA) to 

understand the goals, the decisions that must be made to achieve those goals, and the information 

required to make the decisions. This analysis not only defines the goals associated with traffic 

management, it also identifies the type of information that needs to be easily accessible on the 

GUI to support traffic management activities and provides clear guidance about how that 

information needs to be combined to support optimal decision making. In addition to the GDTA, 

the SAOD process includes a traditional function analysis to define the functions and tasks that 

must be accomplished. To understand the technology perspective, a work domain analysis was 

conducted to model the functional constraints of the SORM systems. The users’ requirements 

and the technology insight were integrated to create a set of information requirements essential 

for the success of the SORM DST. The artifacts resulting from this phase of the project include 

(1) the work domain analysis, (2) the GDTA, (3) the functional analysis and (4) the resultant 

information requirements. 

The second phase of the SAOD process combines the results of the analysis phase with SAOD

principles as well as human factors design guidelines and standards to create common, intuitive, 

goal-based GUI designs. Each design is based on a goal drawn from the GDTA, thereby 
SORM Concept of Operations

72

providing designs that are goal-centric, support the decisions that need to be made relative to that 

goal, and provide the relevant information to support decision making, all in a single view. The 

results of this design are detailed GUI schematics that provide the functionality needed to 

support traffic management activities.

The third phase of the SAOD process entails systematically evaluating the GUI to ensure the 

designs support those involved in traffic management activities. A full evaluation involves a 

variety of metrics that when combined, provide a robust picture of the ease with which the user 

can develop and maintain an appropriately high level of situation awareness, workload 

associated with using the GUI, and performance obtained with the new designs. For this project, 

the measurement phase was limited to two informal GUI evaluation sessions. However, in order 

to provide a path forward for future evaluations of the SORM DST, additional information 

pertaining to low-fidelity cognitive walkthroughs, part task testing, and high-fidelity simulation 

experiments was identified. 

The SORM DST concepts developed during this effort included four designed views (current 

ops, demand, configuration, and balance traffic) and two configurable tile panes (one on each 

side of the display). Full descriptions can be found in the Preliminary GUI Functionality 

Description (ref. 22). Figure C-2 shows a view of the GUI with these tiles presented.

 

Figure C-2. Preliminary GUI design.
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System-Oriented Runway Management Concept of Operations 

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future Next Generation Air Traffic System (NextGen) environments, including research conducted to date. Note that the 

concept is based on the belief that runways are the primary constraint and the decision point for controlling efficiency, but the 

efficiency of runway management must be measured over a wide range of space and time. Implementation of the SORM 

concept is envisioned through a collection of complementary, necessary capabilities collectively focused on ensuring efficient 

arrival and departure traffic management, where that efficiency is measured not only in terms of runway efficiency but in 

terms of the overall trajectories between parking gates and transition fixes. For the more original elements of the 

concept-airport configuration management-this document proposes specific air traffic management (ATM) decision-support 

automation for realizing the concept.

15. SUBJECT TERMS

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