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NASA NTRS2018

Comparison of First-Come First-Served and Optimization Based Scheduling Algorithms for Integrated Departure and Arrival Management

Korea Aerospace Research Institute (KARI) and National Aeronautics and Space Administration (NASA) are investigating scheduling algorithms that will be a part of an integrated arrival and departure management system. Inha University, one of the Korean collaborators of KARI, developed an Extended First-Come First-Served (EFCFS) algorithm that is robust and efficient. However, since the EFCFS algorithm sequentially computes the schedule based on priority, the end results may not be optimal for system efficiency. The approach based on Mixed Integer Linear Programming (MILP) originally developed by NASA and modified by KARI is known to produce better schedules at the expense of computational cost. In this paper, the two different scheduling approaches are compared using common traffic scenarios and constraints at Incheon International Airport. Capabilities to apply weight class based wake turbulence runway separation minima and Miles-in-Trail (MIT) restrictions at selected meter fixes are added to the previously developed EFCFS scheduler. Based on historic data, 40 departures and 20 arrivals are chosen in a one-hour period and 100 scenarios were created by randomly assigning gate numbers, gate departure times, and runway landing times. With the current runway separation requirements, MILP resulted in about ten to twenty percent smaller average delays depending on the constraints. With artificially increased separation minima, the difference between MILP and EFCFS became more noticeable. However, the EFCFS was about ten times faster with smaller variations among different scenarios and constraints. The comparison suggests that the MILP-based algorithm has a small advantage at the current traffic level; however, has potential to be more effective in higher demand or severe weather situations. The EFCFS algorithm may be better suited for real-time applications or investigating larger scale scheduling problems.

air traffic optimization↗

NASA NTRS2015

Terminal Sequencing and Spacing (TSS)

The Federal Aviation Administration's (FAA) Next Generation Air Transportation System (or NextGen) is being designed to support the predicted increases in traffic volume and to increase the capacity, efficiency and safety of the National Airspace System (NAS). The Federal Aviation Administration (FAA) identifies Performance-Based Navigation (PBN) as a key enabling capability of NextGen and is actively publishing PBN procedures at major airports throughout the United States. Standard Terminal Arrival Routes (STARs), procedures, and approaches are designed to facilitate fuel-efficient continuous descent operations. However, their use is limited during periods of high traffic demand due to the complexity of merging multiple streams of aircraft to the same airport. As a result, most arrivals in the Terminal Radar Approach Control (TRACON) area continue to be controlled using radar vectoring and step-down descents, resulting in high workload for controllers and diverting aircraft from efficient PBN trajectories. To address this issue, NASA developed the Terminal Sequencing and Spacing (TSS) system, an advanced arrival management technology that combines time-based scheduling and controller-based precision spacing tools. TSS is a ground-based controller automation tool that facilitates sequencing and merging arrivals on Performance-Based Navigation (PBN) routes, especially during highly congested demand periods. The two main components of TSS are: 1) a scheduler that de-conflicts merging arrivals in the terminal area by computing appropriate arrival times to the runway threshold and upstream terminal merge points, and 2) a set of Controller-Managed Spacing (CMS) decision support tools to efficiently assist schedule conformance. Sixteen high-fidelity human-in-the-loop simulations involving more than five hundred hours of evaluation time, were conducted to mature TSS from proof-of-concept design to a fully functional prototype. Results indicate high controller use and acceptability of the CMS tools as well as improved PBN route conformance (Figure 2). The TSS technology was transferred to the FAA in 2014, and it is targeted for deployment to several busy airports in the U.S. starting in 2018. Potential enhancements to TSS using DataComm will also be presented.

controller-managed spacing↗

NASA NTRS1981

Evaluation of Microwave Landing System (MLS) effect on the delivery performance of a fixed-path metering and spacing system

Metering and spacing (M & S) system's algorithms described assume an aircraft two dimensional are navigation capability. The three navigation systems compared were: very high frequency omnidirectional range/distance measuring equipment (VOR/DME) and ILS, VOR/DME and + or - 40 MLS, and VOR/DME and + or - 60 MLS. Other factors studied were M & S tentative schedule point location, route geometry effects, and approach gate location effects. Summarized results are: the MLS offers some improvement over VOR/DME and ILS if all approach routes contain computer assisted turns; pilot reaction to moving the gate closer to the runway threshold may adversely affect M & S performance; and coupling en route metering to terminal scheduling transfers most of the terminal holding to more full efficient, higher altitude en route delay.

Credeur, L.↗

NASA NTRS2017

Assessing Tactical Scheduler Options for Time-Based Surface Metering

NASA is committed to demonstrating a concept of integrated arrival, departure, and surface operations by 2020 under the Airspace Technology Demonstration 2 (ATD2) sub-project. This will be accomplished starting with a demonstration of flight specific time-based departure metering at Charlotte Douglass International Airport (CLT). ATD2 tactical metering capability is based on NASAs Spot And Runway Departure Advisor (SARDA) which has been tested successfully in human-in-the-loop simulations of CLT. SARDA makes use of surface surveillance data and surface modeling to estimate the earliest takeoff time for each flight active on the airport surface or ready for pushback from the gate. The system then schedules each flight to its assigned runway in order of earliest takeoff time and assigns a target pushback time, displayed to ramp controllers as an advisory gate hold time. The objective of this method of departure metering is to move as much delay as possible to the gate to minimize surface congestion and engine on-time, while keeping sufficient pressure on the runway to maintain throughput. This flight specific approached enables greater flight efficiency and predictability, facilitating trajectory-based operations and surface-airspace integration, which ATD2 aims to achieve.Throughout ATD2 project formulation and system development, researchers have continuously engaged with stakeholders and future users, uncovering key system requirements for tactical metering that SARDA did not address. The SARDA scheduler is updated every 10 seconds using real-time surface surveillance data to ensure the most up-to-date information is used to predict runway usage. However, rapid updates also open the potential for fluctuating advisories, which Ramp controllers at a busy airport like CLT find unacceptable. Therefore, ATD2 tactical metering requires that all advisories freeze once flights are ready so that Ramp controllers may communicate a single hold time when responding to pilot ready calls.

Zelinski, Shannon↗

NASA NTRS2015

Benefit Assessment for Metroplex Tactical Runway Configuration Management (mTRCM) in a Simulated Environment

The System-Oriented Runway Management (SORM) concept is a collection of capabilities focused on a more efficient use of runways while considering all of the factors that affect runway use. Tactical Runway Configuration Management (TRCM), one of the SORM capabilities, provides runway configuration and runway usage recommendations, and monitoring the active runway configuration for suitability given existing factors. This report focuses on the metroplex environment, with two or more proximate airports having arrival and departure operations that are highly interdependent. The myriad of factors that affect metroplex opeations require consideration in arriving at runway configurations that collectively best serve the system as a whole. To assess the metroplex TRCM (mTRCM) benefit, the performance metrics must be compared with the actual historical operations. The historical configuration schedules can be viewed as the schedules produced by subject matter experts (SMEs), and therefore are referred to as the SMEs' schedules. These schedules were obtained from the FAA's Aviation System Performance Metrics (ASPM) database; this is the most representative information regarding runway configuration selection by SMEs. This report focused on a benefit assessment of total delay, transit time, and throughput efficiency (TE) benefits using the mTRCM algorithm at representative volumes for today's traffic at the New York metroplex (N90).

Phojanamongkolkij, Nipa↗

NASA NTRS2012

Optimal Integration of Departure and Arrivals in Terminal Airspace

Coordination of operations with spatially and temporally shared resources such as route segments, fixes, and runways improves the efficiency of terminal airspace management. Problems in this category include scheduling and routing, thus they are normally difficult to solve compared with pure scheduling problems. In order to reduce the computational time, a fast time algorithm formulation using a non-dominated sorting genetic algorithm (NSGA) was introduced in this work and applied to a test case based on existing literature. The experiment showed that new method can solve the whole problem in fast time instead of solving sub-problems sequentially with a window technique. The results showed a 60% or 406 second delay reduction was achieved by sharing departure fixes (more details on the comparison with MILP results will be presented in the final paper). Furthermore, the NSGA algorithm was applied to a problem in LAX terminal airspace, where interactions between 28% of LAX arrivals and 10% of LAX departures are resolved by spatial segregation, which may introduce unnecessary delays. In this work, spatial segregation, temporal segregation, and hybrid segregation were formulated using the new algorithm. Results showed that spatial and temporal segregation approaches achieved similar delay. Hybrid segregation introduced much less delay than the other two approaches. For a total of 9 interacting departures and arrivals, delay reduction varied from 4 minutes to 6.4 minutes corresponding flight time uncertainty from 0 to 60 seconds. Considering the amount of flights that could be affected, total annual savings with hybrid segregation would be significant.

high density terminal↗

NASA NTRS2004

A Fast-Time Simulation Tool for Analysis of Airport Arrival Traffic

The basic objective of arrival sequencing in air traffic control automation is to match traffic demand and airport capacity while minimizing delays. The performance of an automated arrival scheduling system, such as the Traffic Management Advisor developed by NASA for the FAA, can be studied by a fast-time simulation that does not involve running expensive and time-consuming real-time simulations. The fast-time simulation models runway configurations, the characteristics of arrival traffic, deviations from predicted arrival times, as well as the arrival sequencing and scheduling algorithm. This report reviews the development of the fast-time simulation method used originally by NASA in the design of the sequencing and scheduling algorithm for the Traffic Management Advisor. The utility of this method of simulation is demonstrated by examining the effect on delays of altering arrival schedules at a hub airport.

Erzberger, Heinz↗

NASA NTRS2013

Effects of Airport Tower Controller Decision Support Tool on Controllers Head-Up Time

Despite that aircraft positions and movements can be easily monitored on the radar displays at major airports nowadays, it is still important for the air traffic control tower (ATCT) controllers to look outside the window as much as possible to assure safe operations of traffic management. The present paper investigates whether an introduction of the NASA's proposed Spot and Runway Departure Advisor (SARDA), a decision support tool for the ATCT controller, would increase or decrease the controllers' head-up time. SARDA provides the controller departure-release schedule advisories, i.e., when to release each departure aircraft in order to minimize individual aircraft's fuel consumption on taxiways and simultaneously maximize the overall runway throughput. The SARDA advisories were presented on electronic flight strips (EFS). To investigate effects on the head-up time, a human-in-the-loop simulation experiment with two retired ATCT controller participants was conducted in a high-fidelity ATCT cab simulator with 360-degree computer-generated out-the-window view. Each controller participant wore a wearable video camera on a side of their head with the camera facing forward. The video data were later used to calculate their line of sight at each moment and eventually identify their head-up times. Four sessions were run with the SARDA advisories, and four sessions were run without (baseline). Traffic-load levels were varied in each session. The same set of user interface - EFS and the radar displays - were used in both the advisory and baseline sessions to make them directly comparable. The paper reports the findings and discusses their implications.

airport surface operations↗

NASA NTRS2014

Precision Arrival Scheduling for Tactical Reconfiguration

This research adapts the concept of precision arrival scheduling to accommodate reconfiguration operations between two sets of fixed arrival routes modeled for Chicago O'Hare International Airport (ORD). Integrated fixed path routing from en-route to runways was modeled for ORD's top two peak traffic configurations, as well as transition routing between the two configurations. A first-come-first-served multi-point scheduler was adapted to the reconfiguration problem by prioritizing the rescheduling of aircraft within the terminal airspace at the time of reconfiguration notification. Arrival rescheduling was then tested for a range of arrival rates and reconfiguration notification lead-times in fasttime simulation. Reconfigurations with lead-times as short as 10 minutes at a nominal static configuration arrival rate (~25 arrivals per quarter hour) could be accommodated with little impact to throughput. However, as lead-time shortened below 25 minutes, individual aircraft efficiency quickly degraded due to extra flight time at lower altitude and speed. In general, first-come-first-served arrival scheduling on fixed routing for this sample reconfiguration problem is promising if at least 10-15 minutes lead-time is given before the reconfiguration is in effect.

airport reconfiguration↗

NASA NTRS2019

Prediction of Pushback Times and Ramp Taxi Times for Departures at Charlotte Airport

When optimizing the takeoff sequence and schedule for departures at busy airports, it is important to accurately predict the taxi times from gate to runway because those are used to calculate the earliest possible takeoff times. Several airports like Charlotte Douglas International Airport show relatively long taxi times inside the ramp area with large variations, with respect to the travel times in the airport movement area. Also, the pushback process times have not been accurately modeled so far mainly due to the lack of accurate data. The recent deployment of the integrated arrival, departure, and surface traffic management system at Charlotte airport by NASA enables more accurate flight data in the airport surface operations to be obtained. Taking advantage of this system, actual pushback times and ramp taxi times from historical flight data at this airport are analyzed. Based on the analysis, a simple, data-driven prediction model is introduced for estimating pushback times and ramp transit times of individual departure flights. To evaluate the performance of this prediction model, several machine learning techniques are also applied to the same dataset. The prediction results show that the data-driven prediction model is as good as the machine learning algorithms when comparing various prediction performance metrics.

Lee, Hanbong↗

NASA NTRS2019

Prediction of Pushback Times and Ramp Taxi Times for Departures at Charlotte Airport

airport surface operations↗

NASA NTRS1996

The Joint Winter Runway Friction Measurement Program: NASA Perspective

Some background information is given together with the scope and objectives of the 5-year, Joint National Aeronautics & Space Administration (NASA)/Transport Canada (TC)/Federal Aviation Administration (FAA) Winter Runway Friction Measurement Program. The range of the test equipment, the selected test sites and a tentative test program schedule are described. NASA considers the success of this program critical in terms of insuring adequate ground handling performance capability in adverse weather conditions for future aircraft being designed and developed as well as improving the safety of current aircraft ground operations.

Yager, Thomas J.↗

NASA NTRS1975

Further studies of methods for reducing community noise around airports

A simplified method of analysis was used in which all flights at a 'simulated' airport were assumed to operate from one runway in a single direction. For this simulated airport, contours of noise exposure forecast were obtained and evaluated. A flight schedule of the simulated airport which is representative of the 23 major U. S. airports was used. The effect of banning night-time operations by four-engine, narrow-body aircraft in combination with other noise reduction options was studied. The reductions in noise which would occur of two- and three-engine, narrow-body aircraft equipped with a refanned engine was examined. A detailed comparison of the effects of engine cutback on takeoff versus the effects of retrofitting quiet nacelles for narrow-body aircraft was also examined. A method of presenting the effects of various noise reduction options was treated.

Petersen, R. H.↗

NASA NTRS2004

A Multiple Constraint Queuing Model for Predicting Current and Future Terminal Area Capacities

A new queuing model is being developed to evaluate the capacity benefits of several new concepts for terminal airspace operations. The major innovation is the ability to support a wide variety of multiple constraints for modeling the scheduling logic of several concepts. Among the constraints modeled are in-trail separation, separation between aircraft landing on parallel runways, in-trail separation at terminal area entry points, and permissible terminal area flight times.

Meyn, Larry A.↗

NASA NTRS2013

Optimal Integration of Departures and Arrivals in Terminal Airspace

Coordination of operations with spatially and temporally shared resources, such as route segments, fixes, and runways, improves the efficiency of terminal airspace management. Problems in this category are, in general, computationally difficult compared to conventional scheduling problems. This paper presents a fast time algorithm formulation using a non-dominated sorting genetic algorithm (NSGA). It was first applied to a test problem introduced in existing literature. An experiment with a test problem showed that new methods can solve the 20 aircraft problem in fast time with a 65% or 440 second delay reduction using shared departure fixes. In order to test its application in a more realistic and complicated problem, the NSGA algorithm was applied to a problem in LAX terminal airspace, where interactions between 28% of LAX arrivals and 10% of LAX departures are resolved by spatial separation in current operations, which may introduce unnecessary delays. In this work, three types of separations - spatial, temporal, and hybrid separations - were formulated using the new algorithm. The hybrid separation combines both temporal and spatial separations. Results showed that although temporal separation achieved less delay than spatial separation with a small uncertainty buffer, spatial separation outperformed temporal separation when the uncertainty buffer was increased. Hybrid separation introduced much less delay than both spatial and temporal approaches. For a total of 15 interacting departures and arrivals, when compared to spatial separation, the delay reduction of hybrid separation varied between 11% or 3.1 minutes and 64% or 10.7 minutes corresponding to an uncertainty buffer from 0 to 60 seconds. Furthermore, as a comparison with the NSGA algorithm, a First-Come-First-Serve based heuristic method was implemented for the hybrid separation. Experiments showed that the results from the NSGA algorithm have 9% to 42% less delay than the heuristic method with varied uncertainty buffer sizes.

terminal airspace↗

NASA NTRS1971

On optimal scheduling and air traffic control in the near terminal area

A scheme is proposed for automated air traffic control of landing aircraft in the vicinity of the airport. Each aircraft is put under the control of an airport-based computer as soon as it enters the near-terminal area (NTA). Scheduling is done immediately thereafter. The aircraft is given a flight plan which, if followed precisely, will lead it to the runway at a prespecified time. The geometry of the airspace in the NTA is chosen so that delays are executed far from the outer marker, and violations of minimum altitude and lateral separations are avoided. Finally, a solution to the velocity mix problem is proposed.

Sarris, A. H.↗

NASA NTRS2015

SARDA HITL #6 Simulation: System Performance Analysis (Initial Results)

This presentation discusses the results of the 6th human-in-the-loop simulation of the Spot and Runway Departure Advisor (SARDA). SARDA is a research prototype decision support tool for both Air Traffic Control Tower controllers and airlines ramp controllers to assit in controlling surface traffic of a busy airport. Data was collected during the human-in-the-loop simulations of SARDA for ramp operatoins at Charlotte International Airport (Oct-Nov 2014). The performance results include taxi time, taxi delay, total delay, and runway usage.

surface management↗

NASA NTRS2011

TPSAS-NF1676L-12441-DND

The increasing presence of airport surface surveillance technologies has spawned a strong interest in airport surface traffic management research; the vast majority has assumed that the airport’s runway configuration is known and constant. Tactical Runway Configuration Management (TRCM), one component of NASA’s System Oriented Runway Management concept, plans the airport configuration to optimize traffic efficiency for the forecast weather, traffic, and other factors. While planning runway configuration can provide benefit and is required by other automation concepts, larger benefits are possible by planning other airport configuration decisions, such as runway assignment policies, that are currently made manually by controllers. A laboratory prototype of the TRCM algorithm which selects optimal airport configuration schedules has been implemented and studied within a simulation environment. The presentation will describe simulation results for several airports, under various weather and traffic conditions. The sequence of airport configurations recommended by TRCM result in significantly less delay than the airport configurations that were actually used by controllers, illustrating both the potential benefit from airport configuration optimization and the ability of TRCM to provide effective airport configuration schedules. The application to several, distinct airports demonstrates the approach is capable of handling the differences between airports with a common algorithm, while providing decision support that respects the current procedures at those airports. Consequently, TRCM is able to be deployed to any airport within the current National Airspace System. The TRCM algorithmic approach is also extensible to future operational scenarios. NASA is in the process of transferring the initial TRCM technology to the FAA. Future research will extend the concept and algorithm to provide coordinated plans for metroplex airports and study NextGen applications.

Stephen Atkins↗