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NASA NTRS2016

Scheduler Design Criteria: Requirements and Considerations

This presentation covers fundamental requirements and considerations for developing schedulers in airport operations. We first introduce performance and functional requirements for airport surface schedulers. Among various optimization problems in airport operations, we focus on airport surface scheduling problem, including runway and taxiway operations. We then describe a basic methodology for airport surface scheduling such as node-link network model and scheduling algorithms previously developed. Next, we explain how to design a mathematical formulation in more details, which consists of objectives, decision variables, and constraints. Lastly, we review other considerations, including optimization tools, computational performance, and performance metrics for evaluation.

NASA-KAIA/KARI research collaboration↗

NASA NTRS2019

Scheduling and Airport Taxiway Path Planning Under Uncertainty

Congestion and uncertainty on the airport surface are major constraints to the available capacity of the air transport system. This project is to study the problem of planning and scheduling airport surface movement at large airports. Specifically, we focus on the departure time scheduling and taxiway path planning of multiple aircraft under uncertainty. We also developed a simulation tool that is capable of simulating aircraft movement along the taxiway and possible uncertainty during the movement.

Li, Jiaoyang↗

NASA NTRS2019

Modeling Deicing Operations in Departure Scheduling Using Fast Time Simulation

In winter snow conditions, aircraft need inspection for deicing service before takeoff. Deicing service is a procedure to remove frost, ice, slush, or snow from aircraft for safe operation. Deicing operations vary by airport in many ways. Some airports have designated deicing zones, whereas some use a closed runway or terminal area to perform the procedure. Nonetheless, deicing operations add extra workloads to controllers, and cause increased taxi traffic on the ground. NASA and Korea Aerospace Research Institute (KARI) have been collaborating to model deicing operations at Incheon International Airport (ICN). This paper describes the deicing model and the study of deicing operations in departure scheduling using fast time simulations. The deicing model uses a heuristic algorithm for deicing zone assignment. In the fast time simulations, the model uses probability distributions derived from actual operation data to model deicing request and deicing zone time. It is envisioned that such a deicing model can be useful in airport surface scheduling to provide decision support and improve traffic management performance in winter snow operations.

modeling and simulation↗

NASA NTRS2019

Modeling Deicing Operations in Departure Scheduling using Fast Time Simulation

surface operation↗

NASA NTRS2016

Operational Characteristics Identification and Simulation Model Verification for Incheon International Airport

Incheon International Airport (ICN) is one of the hub airports in East Asia. Airport operations at ICN have been growing more than 5% per year in the past five years. According to the current airport expansion plan, a new passenger terminal will be added and the current cargo ramp will be expanded in 2018. This expansion project will bring 77 new stands without adding a new runway to the airport. Due to such continuous growth in airport operations and future expansion of the ramps, it will be highly likely that airport surface traffic will experience more congestion, and therefore, suffer from efficiency degradation. There is a growing awareness in aviation research community of need for strategic and tactical surface scheduling capabilities for efficient airport surface operations. Specific to ICN airport operations, a need for A-CDM (Airport - Collaborative Decision Making) or S-CDM(Surface - Collaborative Decision Making), and controller decision support tools for efficient air traffic management has arisen since several years ago. In the United States, there has been independent research efforts made by academia, industry, and government research organizations to enhance efficiency and predictability of surface operations at busy airports. Among these research activities, the Spot and Runway Departure Advisor (SARDA) developed and tested by National Aeronautics and Space Administration (NASA) is a decision support tool to provide tactical advisories to the controllers for efficient surface operations. The effectiveness of SARDA concept, was successfully verified through the human-in-the-loop (HITL) simulations for both spot release and runway operations advisories for ATC Tower controllers of Dallas/Fort Worth International Airport (DFW) in 2010 and 2012, and gate pushback advisories for the ramp controller of Charlotte/Douglas International Airport (CLT) in 2014. The SARDA concept for tactical surface scheduling is further enhanced and is being integrated into NASA's Airspace Technology Demonstration - 2 (ATD-2) project for technology demonstration of Integrated Arrival/Departure/Surface (ADS) operations at CLT. This study is a part of the international research collaboration between KAIA (Korea Agency for Infrastructure Technology Advancement)/KARI (Korea Aerospace Research Institute) and NASA, which is being conducted to validate the effectiveness of SARDA concept as a controller decision support tool for departure and surface management of ICN. This paper presents the preliminary results of the collaboration effort. It includes investigation of the operational environment of ICN, data analysis for identification of the operational characteristics of the airport, construction and verification of airport simulation model using Surface Operations Simulator and Scheduler (SOSS), NASA's fast-time simulation tool.

scheduling↗

NASA NTRS2016

Operational Characteristics Identification and Simulation Model Verification for Incheon International Airport

Incheon International Airport (ICN) is one of the hub airports in East Asia. Airport operations at ICN have been growing more than 5 percent per year in the past five years. According to the current airport expansion plan, a new passenger terminal will be added and the current cargo ramp will be expanded in 2018. This expansion project will bring 77 new stands without adding a new runway to the airport. Due to such continuous growth in airport operations and future expansion of the ramps, it will be highly likely that airport surface traffic will experience more congestion, and therefore, suffer from efficiency degradation. There is a growing awareness in aviation research community of need for strategic and tactical surface scheduling capabilities for efficient airport surface operations. Specific to ICN airport operations, a need for A-CDM (Airport - Collaborative Decision Making) or S-CDM (Surface - Collaborative Decision Making), and controller decision support tools for efficient air traffic management has arisen since several years ago. In the United States, there has been independent research efforts made by academia, industry, and government research organizations to enhance efficiency and predictability of surface operations at busy airports. Among these research activities, the Spot and Runway Departure Advisor (SARDA) developed and tested by National Aeronautics and Space Administration (NASA) is a decision support tool to provide tactical advisories to the controllers for efficient surface operations. The effectiveness of SARDA concept, was successfully verified through the human-in-the-loop (HITL) simulations for both spot release and runway operations advisories for ATC Tower controllers of Dallas-Fort Worth International Airport (DFW) in 2010 and 2012, and gate pushback advisories for the ramp controller of Charlotte-Douglas International Airport (CLT) in 2014. The SARDA concept for tactical surface scheduling is further enhanced and is being integrated into NASA's Airspace Technology Demonstration-2 (ATD-2) project for technology demonstration of Integrated Arrival-Departure-Surface (IADS) operations at CLT. This study is a part of the international research collaboration between KAIA (Korea Agency for Infrastructure Technology Advancement), KARI (Korea Aerospace Research Institute) and NASA, which is being conducted to validate the effectiveness of SARDA concept as a controller decision support tool for departure and surface management of ICN. This paper presents the preliminary results of the collaboration effort. It includes investigation of the operational environment of ICN, data analysis for identification of the operational characteristics of the airport, construction and verification of airport simulation model using Surface Operations Simulator and Scheduler (SOSS), NASA's fast-time simulation tool.

surface operations analysis↗

NASA NTRS2019

Alternatives for Scheduling Departures for Efficient Surface Metering in ATD-2: Exploration in a Human-in-the-Loop Simulation

A Human-in-the-Loop (HITL) simulation was conducted to explore whether Ramp Controllers at Charlotte Douglas International Airport (CLT) could both release departing aircraft at an advised time at the gate and also meet an advised time at the spot, where Air Traffic Control (ATC) takes control. Three conditions were compared: (1) Baseline, with no scheduling advisories, (2) instructions to meet advisory times at the gate only, and (3) instructions to meet advisory times at both the gate and the spot. Surprisingly, results showed increased compliance with advisories at the spot in the second condition. This was likely due to increased ramp congestion in the third condition as well as higher Ramp Controller workload and lower situation awareness. Instructing Ramp Controllers to meet scheduling times at the spots, in addition to the gates, is therefore not likely to improve surface scheduling predictability at CLT and may indeed worsen it.

airport surface scheduling↗

NASA NTRS2017

Initial Data Analysis Results for ATD-2 ISAS HITL Simulation

To evaluate the operational procedures and information requirements for the core functional capabilities of the ATD-2 project, such as tactical surface metering tool, APREQ-CFR procedure, and data element exchanges between ramp and tower, human-in-the-loop (HITL) simulations were performed in March, 2017. This presentation shows the initial data analysis results from the HITL simulations. With respect to the different runway configurations and metering values in tactical surface scheduler, various airport performance metrics were analyzed and compared. These metrics include gate holding time, taxi-out in time, runway throughput, queue size and wait time in queue, and TMI flight compliance. In addition to the metering value, other factors affecting the airport performance in the HITL simulation, including run duration, runway changes, and TMI constraints, are also discussed.

HITL simulation↗

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 NTRS2018

Impact of Data Exchange Provided by ATD2 Tools at Charlotte-Douglas International Airport

Data Exchange and Integration is necessary for progress towards an Integrated Arrival, Departure, and Surface (IADS) traffic management capability. In collaboration with the FAA, NASA has introduced new data exchange elements to Charlotte-Douglas International Airport air traffic facilities, including the American Airlines ramp, as part of the Airspace Technology Demonstration 2 (ATD2). This paper describes the new tools that deliver these elements, and the human factors impact of the tools as measured by post-bank surveys. Workload was unaffected by ATD2 tool use, and situational awareness was improved in the Tower and with Ramp controllers in the second round of surveys. Respondents described their tools as more helpful if they included ATD2 tools 1) in the Tower for insuring compliance for aircraft under a Traffic Management Initiative, 2) in the TRACON when actively used for many TRACON tasks, and 3) in the Ramp in the second round of surveys.

and surface traffic management; human factors asse↗

NASA NTRS2018

Airspace Technology Demonstration 2 (ATD-2) Phase 1 Concept of Use (ConUse)

This document presents an operational Concept of Use (ConUse) for the Phase 1 Baseline Integrated Arrival, Departure, and Surface (IADS) prototype system of NASA's Airspace Technology Demonstration 2 (ATD-2) sub-project, which began demonstration in 2017 at Charlotte Douglas International Airport (CLT). NASA is developing the IADS system under the ATD-2 sub-project in coordination with the Federal Aviation Administration (FAA) and aviation industry partners. The primary goal of ATD-2 sub-project is to improve the predictability and the operational efficiency of the air traffic system in metroplex environments, through the enhancement, development, and integration of the nation's most advanced and sophisticated arrival, departure, and surface prediction, scheduling, and management systems. The ATD-2 effort is a five-year research activity through 2020. The initial phase of the ATD-2 sub-project, which is the focus of this document, will demonstrate the Phase 1 Baseline IADS capability at CLT in 2017. The Phase 1 Baseline IADS capabilities of the ATD-2 sub-project consists of: (a) Strategic and tactical surface scheduling to improve efficiency and predictability of airport surface operations, (b) Tactical departure scheduling to enhance merging of departures into overhead traffic streams via accurate predictions of takeoff times and automated coordination between the Airport Traffic Control Tower (ATCT, or Tower) and the Air Route Traffic Control Center (ARTCC, or Center), (c) Improvements in departure surface demand predictions in Time Based Flow Management (TBFM), (d) A prototype Electronic Flight Data (EFD) system provided by the FAA via the Terminal Flight Data Manager (TFDM) early implementation effort, and (e) Improved situational awareness and demand predictions through integration with the Traffic Flow Management System (TFMS), TBFM, and TFDM (3Ts) for electronic data integration and exchange, and an on-screen dashboard displaying pertinent analytics in real-time. The surface scheduling and metering element of the capability is consistent with the Surface CDM Concept of Operations published in 2014 by the FAA Surface Operations Directorate.1 Upon successful demonstration of the Phase 1 Baseline IADS capability, follow-on demonstrations of the matured IADS traffic management capabilities will be conducted in the 2018-2020 timeframe. At the end of each phase of the demonstrations, NASA will transfer the ATD-2 sub-project technology to the FAA and industry partners.

integrated arrival↗

NASA NTRS2016

Departure Queue Prediction for Strategic and Tactical Surface Scheduler Integration

A departure metering concept to be demonstrated at Charlotte Douglas International Airport (CLT) will integrate strategic and tactical surface scheduling components to enable the respective collaborative decision making and improved efficiency benefits these two methods of scheduling provide. This study analyzes the effect of tactical scheduling on strategic scheduler predictability. Strategic queue predictions and target gate pushback times to achieve a desired queue length are compared between fast time simulations of CLT surface operations with and without tactical scheduling. The use of variable departure rates as a strategic scheduler input was shown to substantially improve queue predictions over static departure rates. With target queue length calibration, the strategic scheduler can be tuned to produce average delays within one minute of the tactical scheduler. However, root mean square differences between strategic and tactical delays were between 12 and 15 minutes due to the different methods the strategic and tactical schedulers use to predict takeoff times and generate gate pushback clearances. This demonstrates how difficult it is for the strategic scheduler to predict tactical scheduler assigned gate delays on an individual flight basis as the tactical scheduler adjusts departure sequence to accommodate arrival interactions. Strategic/tactical scheduler compatibility may be improved by providing more arrival information to the strategic scheduler and stabilizing tactical scheduler changes to runway sequence in response to arrivals.

departure scheduling↗

NASA NTRS2015

SOSS User Guide

This User Guide describes SOSS (Surface Operations Simulator and Scheduler) software build and graphic user interface. SOSS is a desktop application that simulates airport surface operations in fast time using traffic management algorithms. It moves aircraft on the airport surface based on information provided by scheduling algorithm prototypes, monitors separation violation and scheduling conformance, and produces scheduling algorithm performance data.

air traffic control↗

NASA NTRS2016

Methods for Determining Aircraft Surface State at Lesser-Equipped Airports

Tactical departure scheduling within a terminal airspace must accommodate a wide spectrum of surveillance and communication capabilities at multiple airports. The success of such a scheduler is highly dependent upon the knowledge of a departure's state while it is still on the surface. Airports within a common Terminal RAdar CONtrol (TRACON) airspace possess varying levels of surface surveillance infrastructure which directly impacts uncertainties in wheels-off times. Large airports have access to surface surveillance data, which is shared with the TRACON, while lesser-equipped airports still rely solely on controllers in Air Traffic Control Towers (Towers). Coordination between TRACON and Towers can be greatly enhanced when the TRACON controller has access to the surface surveillance and the associated decision-support tools at well-equipped airports. Similar coordination at lesser-equipped airports is still based on verbal communications. This paper investigates possible methods to reduce the uncertainty in wheels-off time predictions at the lesser-equipped airports through the novel use of Over-the-Air (OTA) data transmissions. We also discuss the methods and equipment used to collect sample data at lesser-equipped airports within a large US TRACON, as well as the data evaluation to determine if meaningful information can be extracted from it.

departure scheduling↗

NASA NTRS2016

Benefit Opportunities for Integrated Surface and Airspace Departure Scheduling: A Study of Operations at Charlotte-Douglas International Airport

NASA is collaborating with the FAA and aviation industry to develop and demonstrate new capabilities that integrate arrival, departure, and surface air-traffic operations. The concept relies on trajectory-based departure scheduling and collaborative decision making to reduce delays and uncertainties in taxi and climb operations. The paper describes the concept and benefit mechanisms aimed at improving flight efficiency and predictability while maintaining or improving operational throughput. The potential impact of the technology is studied and discussed through a quantitative analysis of relevant shortfalls at the site identified for initial deployment and demonstration in 2017: Charlotte-Douglas International Airport. Results from trajectory analysis indicate substantial opportunity to reduce taxi delays for both departures and arrivals by metering departures at the gate in a manner that maximizes throughput while adhering to takeoff restrictions due mostly to airspace constraints. Substantial taxi-out delay reduction is shown for flights subject to departure restrictions stemming from traffic flow management initiatives. Opportunities to improve the predictability of taxi, takeoff, and climb operations are examined and their potential impact on airline scheduling decisions and air-traffic forecasting is discussed. In addition, the potential to improve throughput with departure scheduling that maximizes use of available runway and airspace capacity is analyzed.

air traffic management↗

NASA NTRS2011

Characterization of Tactical Departure Scheduling in the National Airspace System

This paper discusses and analyzes current day utilization and performance of the tactical departure scheduling process in the National Airspace System (NAS) to understand the benefits in improving this process. The analysis used operational air traffic data from over 1,082,000 flights during the month of January, 2011. Specific metrics included the frequency of tactical departure scheduling, site specific variances in the technology's utilization, departure time prediction compliance used in the tactical scheduling process and the performance with which the current system can predict the airborne slot that aircraft are being scheduled into from the airport surface. Operational data analysis described in this paper indicates significant room for improvement exists in the current system primarily in the area of reduced departure time prediction uncertainty. Results indicate that a significant number of tactically scheduled aircraft did not meet their scheduled departure slot due to departure time uncertainty. In addition to missed slots, the operational data analysis identified increased controller workload associated with tactical departures which were subject to traffic management manual re-scheduling or controller swaps. An analysis of achievable levels of departure time prediction accuracy as obtained by a new integrated surface and tactical scheduling tool is provided to assess the benefit it may provide as a solution to the identified shortfalls. A list of NAS facilities which are likely to receive the greatest benefit from the integrated surface and tactical scheduling technology are provided.

Capps, Alan↗

NASA NTRS2013

Spot and Runway Departure Advisor

The Spot and Runway Departure Advisor (SARDA) is a research prototype of a decision support tool for ATC tower controllers to assist in manging and controlling traffic on the surface of an airport. SARDA employs a scheduler to generate an optimal runway schedule and gate push-back - spot release sequence and schedule that improves efficiency of surface operations. The advisories for ATC tower controllers are displayed on an Electronic Flight Strip (EFS) system. The human-in-the-loop simulation of the SARDA tool was conducted for east operations of Dallas-Ft. Worth International Airport (DFW) to evaluate performance of the SARDA tool and human factors, such as situational awareness and workload. The results indicates noticeable taxi delay reduction and fuel savings by using the SARDA tool. Reduction in controller workload were also observed throughout the scenario runs. The future plan includes modeling and simulation of the ramp operations of the Charlotte International Airport, and develop a decision support tool for the ramp controllers.

decision support tool↗

NASA NTRS2019

Fast-Time Simulation for Evaluating the Impact of Estimated Flight Ready Time Uncertainty on Surface Metering

NASA has been developing and demonstrating new concepts and technologies for Integrated Arrival, Departure, and Surface (IADS) traffic management capabilities under the Airspace Technology Demonstration 2 (ATD-2) project. One of the IADS capabilities in the ATD-2 project is surface metering enabled by a tactical surface scheduler to provide controllers with the pushback advisories for departures at gates. The tactical surface scheduler uses the estimated flight ready times provided by airlines, called Earliest Off-Block Times (EOBTs), as input to calculate the target off-block times for pushback advisories. However, the EOBTs are often inaccurate and deviate from the actual flight ready times, which may reduce the benefits of surface metering. In this paper, a linear regression model is developed to model the EOBT uncertainty distribution over time based on actual EOBT data collected at Charlotte airport. This EOBT model is integrated with a tactical surface scheduler and a fast-time simulation tool. To evaluate the impact of the EOBT accuracy on airport surface operations, fast-time simulations are implemented for selected traffic scenarios under different levels of modelled EOBT accuracy. The simulation results show that the EOBT uncertainty affects several performance metrics related to the surface metering, such as gate hold, taxi time reduction, and target takeoff time predictability, which in turn influences ATD-2's scheduler performance.

tactical surface scheduler↗