Search NASA⌕ Search

SEARCH · Search NASA

Results for “departure scheduling”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2

Real Time Metrics and Analysis of Integrated Arrival, Departure, and Surface Operations

To address the Integrated Arrival, Departure, and Surface (IADS) challenge, NASA is developing and demonstrating trajectory-based departure automation under a collaborative effort with the FAA and industry known Airspace Technology Demonstration 2 (ATD-2). ATD-2 builds upon and integrates previous NASA research capabilities that include the Spot and Runway Departure Advisor (SARDA), the Precision Departure Release Capability (PDRC), and the Terminal Sequencing and Spacing (TSAS) capability. As trajectory-based departure scheduling and collaborative decision making tools are introduced in order to reduce delays and uncertainties in taxi and climb operations across the National Airspace System, users of the tools across a number of roles benefit from a real time system that enables common situational awareness. A real time dashboard was developed to inform and present users notifications and integrated information regarding airport surface operations. The dashboard is a supplement to capabilities and tools that incorporate arrival, departure, and surface air-traffic operations concepts in a NextGen environment. In addition to shared situational awareness, the dashboard offers the ability to compute real time metrics and analysis to inform users about capacity, predictability, and efficiency of the system as a whole. This paper describes the architecture of the real time dashboard as well as an initial proposed set of metrics. The potential impact of the real time dashboard is studied at the site identified for initial deployment and demonstration in 2017: Charlotte-Douglas International Airport (CLT). The architecture of implementing such a tool as well as potential uses are presented for operations at CLT. Metrics computed in real time illustrate the opportunity to provide common situational awareness and inform users of system delay, throughput, taxi time, and airport capacity. In addition, common awareness of delays and the impact of takeoff and departure restrictions stemming from traffic flow management initiatives are explored. The potential of the real time tool to inform users of the predictability and efficiency of using a trajectory-based departure scheduling system is also discussed.

integrated arrival departure surface operations↗

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↗

Traffic Flow Analysis for Package Delivery Drones using a Queueing Model

A key component of the small unmanned aircraft systems traffic management ecosystem is the design of scalable algorithms for strategic deconfliction of drones prior to takeoff. In this work, we focus on efficient flow management of drones on a network of intersecting edges subject to two kinds of spacing constraints: 1) between any two adjacent vehicles on an edge and 2) between any two vehicles on two different edges arriving one after the other at an intersection. The spacing is designed to enable non-intersection of operational volumes corresponding to two different vehicles thereby properly separating the vehicles inside each volume. For simplicity, we assume a constant ground speed for the drones and fixed dimensions for the operational volume blocks. The deconfliction is managed by adjusting the takeoff time of the drones, thereby regulating their arrival time at various crossing waypoints in the network. This framework allows us to study the maximum flow (throughput) of vehicles on a network of edges connecting depots to drop off sites subject to the temporal spacing constraints. The departure scheduling of individual drones results in a combinatorial optimization problem. To alleviate this, we solve a max-flow formulation and use queueing theory to simplify the analysis and provide upper bounds to the underlying optimization problem for individual drone departure scheduling. Our results indicate that throughput drops rapidly after the density of drones in the network passes the max-flow limits.

Alexey A Munishkin↗

Real Time Metrics and Analysis of Integrated Arrival, Departure, and Surface Operations

A real time dashboard was developed in order to inform and present users notifications and integrated information regarding airport surface operations. The dashboard is a supplement to capabilities and tools that incorporate arrival, departure, and surface air-traffic operations concepts in a NextGen environment. As trajectory-based departure scheduling and collaborative decision making tools are introduced in order to reduce delays and uncertainties in taxi and climb operations across the National Airspace System, users across a number of roles benefit from a real time system that enables common situational awareness. In addition to shared situational awareness the dashboard offers the ability to compute real time metrics and analysis to inform users about capacity, predictability, and efficiency of the system as a whole. This paper describes the architecture of the real time dashboard as well as an initial set of metrics computed on operational data. The potential impact of the real time dashboard is studied at the site identified for initial deployment and demonstration in 2017; Charlotte-Douglas International Airport. Analysis and metrics computed in real time illustrate the opportunity to provide common situational awareness and inform users of metrics across delay, throughput, taxi time, and airport capacity. In addition, common awareness of delays and the impact of takeoff and departure restrictions stemming from traffic flow management initiatives are explored. The potential of the real time tool to inform the predictability and efficiency of using a trajectory-based departure scheduling system is also discussed.

integrated arrival departure surface operations↗

Anchorage Arrival Scheduling Under Off-Nominal Weather Conditions

Weather can cause flight diversions, passenger delays, additional fuel consumption and schedule disruptions at any high volume airport. The impacts are particularly acute at the Ted Stevens Anchorage International Airport in Anchorage, Alaska due to its importance as a major international portal. To minimize the impacts due to weather, a multi-stage scheduling process is employed that is iteratively executed, as updated aircraft demand and/or airport capacity data become available. The strategic scheduling algorithm assigns speed adjustments for flights that originate outside of Anchorage Center to achieve the proper demand and capacity balance. Similarly, an internal departure-scheduling algorithm assigns ground holds for pre-departure flights that originate from within Anchorage Center. Tactical flight controls in the form of airborne holding are employed to reactively account for system uncertainties. Real-world scenarios that were derived from the January 16, 2012 Anchorage visibility observations and the January 12, 2012 Anchorage arrival schedule were used to test the initial implementation of the scheduling algorithm in fast-time simulation experiments. Although over 90% of the flights in the scenarios arrived at Anchorage without requiring any delay, pre-departure scheduling was the dominant form of control for Anchorage arrivals. Additionally, tactical scheduling was used extensively in conjunction with the pre-departure scheduling to reactively compensate for uncertainties in the arrival demand. For long-haul flights, the strategic scheduling algorithm performed best when the scheduling horizon was greater than 1,000 nmi. With these long scheduling horizons, it was possible to absorb between ten and 12 minutes of delay through speed control alone. Unfortunately, the use of tactical scheduling, which resulted in airborne holding, was found to increase as the strategic scheduling horizon increased because of the additional uncertainty in the arrival times of the aircraft. Findings from these initial experiments indicate that it is possible to schedule arrivals into Anchorage with minimal delays under low-visibility conditions with less disruption to high-cost, international flights.

Grabbe, Shon↗

Objective Measurement Assessment of Departure Advisories for Ramp Controllers from a Human-In-The-Loop Simulation

NASA has developed and demonstrated an integrated arrival, departure, and surface concept and technology for efficient air traffic management in busy terminal environments under the Airspace Technology Demonstration 2 (ATD-2) subproject. In April/May 2019, NASA conducted a human-in-the-loop (HITL) simulation with ramp and tower controllers having experience at Dallas/Fort Worth International Airport (DFW). The purpose of this HITL was to evaluate the impacts of various surface metering goals in ramp operations at DFW and test new features of the ATD-2 ramp controller decision support tools. This paper evaluates the quantitative metrics from the simulation results related to airport performance and surface metering given various departure scheduling advisories for ramp controllers. The objective measurements compared include the controller’s compliance with the target times for pushback and spot arrival, the number of metered flights, aircraft gate hold and taxi time, runway throughput, and the number of aircraft on the surface. The simulation results show that there were no statistically significant benefits from surface metering at DFW for airport performance due to several simulation artifacts notably different from real operations. Considering controller workload and situation awareness, following either gate pushback or spot arrival advisory could be a better metering option than utilizing both advisories when surface metering is applied at DFW.

airport ramp traffic control decision support↗

Runway Operations Planning: A Two-Stage Heuristic Algorithm

The airport runway is a scarce resource that must be shared by different runway operations (arrivals, departures and runway crossings). Given the possible sequences of runway events, careful Runway Operations Planning (ROP) is required if runway utilization is to be maximized. From the perspective of departures, ROP solutions are aircraft departure schedules developed by optimally allocating runway time for departures given the time required for arrivals and crossings. In addition to the obvious objective of maximizing throughput, other objectives, such as guaranteeing fairness and minimizing environmental impact, can also be incorporated into the ROP solution subject to constraints introduced by Air Traffic Control (ATC) procedures. This paper introduces a two stage heuristic algorithm for solving the Runway Operations Planning (ROP) problem. In the first stage, sequences of departure class slots and runway crossings slots are generated and ranked based on departure runway throughput under stochastic conditions. In the second stage, the departure class slots are populated with specific flights from the pool of available aircraft, by solving an integer program with a Branch & Bound algorithm implementation. Preliminary results from this implementation of the two-stage algorithm on real-world traffic data are presented.

Anagnostakis, Ioannis↗

Runway Operations Planning: A Two-Stage Solution Methodology

The airport runway is a scarce resource that must be shared by different runway operations (arrivals, departures and runway crossings). Given the possible sequences of runway events, careful Runway Operations Planning (ROP) is required if runway utilization is to be maximized. Thus, Runway Operations Planning (ROP) is a critical component of airport operations planning in general and surface operations planning in particular. From the perspective of departures, ROP solutions are aircraft departure schedules developed by optimally allocating runway time for departures given the time required for arrivals and crossings. In addition to the obvious objective of maximizing throughput, other objectives, such as guaranteeing fairness and minimizing environmental impact, may be incorporated into the ROP solution subject to constraints introduced by Air Traffic Control (ATC) procedures. Generating optimal runway operations plans was approached in with a 'one-stage' optimization routine that considered all the desired objectives and constraints, and the characteristics of each aircraft (weight class, destination, Air Traffic Control (ATC) constraints) at the same time. Since, however, at any given point in time, there is less uncertainty in the predicted demand for departure resources in terms of weight class than in terms of specific aircraft, the ROP problem can be parsed into two stages. In the context of the Departure Planner (OP) research project, this paper introduces Runway Operations Planning (ROP) as part of the wider Surface Operations Optimization (SOO) and describes a proposed 'two stage' heuristic algorithm for solving the Runway Operations Planning (ROP) problem. Focus is specifically given on including runway crossings in the planning process of runway operations. In the first stage, sequences of departure class slots and runwy crossings slots are generated and ranked based on departure runway throughput under stochastic conditions. In the second stage, the departure class slots are populated with specific flights from the pool of available aircraft, by solving an integer program. Preliminary results from the algorithm implementation on real-world traffic data are included.

Anagnostakis, Ioannis↗

Scheduling and Separating Departures Crossing Arrival Flows in Shared Airspace

Flight efficiency and reduction of flight delays are among the primary goals of NextGen. In this paper, we propose a concept of shared airspace where departures fly across arrival flows, provided gaps are available in these flows. We have explored solutions to separate departures temporally from arrival traffic and pre-arranged procedures to support controllers' decisions. We conducted a Human-in-the-Loop simulation and assessed the efficiency and safety of 96 departures from the San Jose airport (SJC) climbing across the arrival airspace of the Oakland and San Francisco arrival flows. In our simulation, the SJC tower had a tool to schedule departures to fly across predicted gaps in the arrival flow. When departures were mistimed and separation could not be ensured, a safe but less efficient route was provided to the departures to fly under the arrival flows. A coordination using a point-out procedure allowed the arrival controller to control the SJC departures right after takeoff. We manipulated the accuracy of departure time (accurate vs. inaccurate) as well as which sector took control of the departures after takeoff (departure vs. arrival sector) in a 2x2 full factorial plan. Results show that coordination time decreased and climb efficiency increased when the arrival sector controlled the aircraft right after takeoff. Also, climb efficiency increased when the departure times were more accurate. Coordination was shown to be a critical component of tactical operations in shared airspace. Although workload, coordination, and safety were judged by controllers as acceptable in the simulation, it appears that in the field, controllers would need improved tools and coordination procedures to support this procedure.

shared airspace↗

Coordination between Federated Scheduling and Conflict Resolution in UAM Operations

This work proposes a federated scheduling algorithm and explores two mechanisms for coordinating federated scheduling and conflict resolution functions - two core traffic management functions in urban air mobility operations. A federated scheduling algorithm is first developed, together with data that needs to be shared among schedulers. Two mechanisms for coordinating scheduling and conflict resolution functions are then introduced and studied as conflicts in high-density operations may not be completely resolved by conflict resolution function alone. The first coordination mechanism is constructed based on the arrival scheduler at the destination and another one utilizes the departure scheduler at the origin. Experiments and trade space studies are conducted to compare these two mechanisms using fast-time traffic simulations. Results show that both mechanisms perform well in coordinating scheduling and conflict resolution functions and helping resolve all potential conflicts. Experiments also show that with proper parameter selection, both mechanisms can achieve better efficiency (less delay) while maintaining zero losses of separation.

Federated scheduling↗

Coordination between Federated Scheduling and Conflict Resolution in UAM Operations

This work proposes a federated scheduling algorithm and explores two mechanisms for coordinating federated scheduling and conflict resolution functions - two core traffic management functions in urban air mobility operations. A federated scheduling algorithm is first developed, together with data that needs to be shared among schedulers. Two mechanisms for coordinating scheduling and conflict resolution functions are then introduced and studied as conflicts in high-density operations may not be completely resolved by conflict resolution function alone. The first coordination mechanism is constructed based on the arrival scheduler at the destination and another one utilizes the departure scheduler at the origin. Experiments and trade space studies are conducted to compare these two mechanisms using fast-time traffic simulations. Results show that both mechanisms perform well in coordinating scheduling and conflict resolution functions and helping resolve all potential conflicts. Experiments also show that with proper parameter selection, both mechanisms can achieve better efficiency (less delay) while maintaining zero losses of separation.

Federated scheduling↗

Electronic Departure Approval Requests in ATD-2 Daily Operations

The NASA Airspace Technology Demonstration 2 project is investigating Integrated Arrival-Departure-Surface air traffic management through progressive refinement of a surface air traffic management system fielded at Charlotte-Douglas International Airport. Among the areas under study are departure release-time approval request (APREQ) traffic management initiatives. Scheduling departures at downstream points and complying with approved departure release times helps flights fit smoothly into busy traffic streams. This paper presents a review of APREQ operations and compliance data from daily electronic APREQ negotiations over fourteen months beginning in January 2018. It describes APREQ-compliance improvements observed as the electronic negotiation process has matured and discusses contributing factors, including renegotiation of departure release times.

Call for release↗

Analyzing Double Delays at Newark Liberty International Airport

When weather or congestion impacts the National Airspace System, multiple different Traffic Management Initiatives can be implemented, sometimes with unintended consequences. One particular inefficiency that is commonly identified is in the interaction between Ground Delay Programs (GDPs) and time based metering of internal departures, or TMA scheduling. Internal departures under TMA scheduling can take large GDP delays, followed by large TMA scheduling delays, because they cannot be easily fitted into the overhead stream. In this paper we examine the causes of these double delays through an analysis of arrival operations at Newark Liberty International Airport (EWR) from June to August 2010. Depending on how the double delay is defined between 0.3 percent and 0.8 percent of arrivals at EWR experienced double delays in this period. However, this represents between 21 percent and 62 percent of all internal departures in GDP and TMA scheduling. A deep dive into the data reveals that two causes of high internal departure scheduling delays are upstream flights making up time between their estimated departure clearance times (EDCTs) and entry into time based metering, which undermines the sequencing and spacing underlying the flight EDCTs, and high demand on TMA, when TMA airborne metering delays are high. Data mining methods (currently) including logistic regression, support vector machines and K-nearest neighbors are used to predict the occurrence of double delays and high internal departure scheduling delays with accuracies up to 0.68. So far, key indicators of double delay and high internal departure scheduling delay are TMA virtual runway queue size, and the degree to which estimated runway demand based on TMA estimated times of arrival has changed relative to the estimated runway demand based on EDCTs. However, more analysis is needed to confirm this.

traffic management advisor↗

Precision Departure Release Capability (PDRC) Overview and Results: NASA to FAA Research Transition

NASA researchers developed the Precision Departure Release Capability (PDRC) concept to improve the tactical departure scheduling process. The PDRC system is comprised of: 1) a surface automation system that computes ready time predictions and departure runway assignments, 2) an en route scheduling automation tool that uses this information to estimate ascent trajectories to the merge point and computes release times and, 3) an interface that provides two-way communication between the two systems. To minimize technology transfer issues and facilitate its adoption by TMCs and Frontline Managers (FLM), NASA developed the PDRC prototype using the Surface Decision Support System (SDSS) for the Tower surface automation tool, a research version of the FAA TMA (RTMA) for en route automation tool and a digital interface between the two DSTs to facilitate coordination.

PDRC↗

Distributed Schemes for Integrated Arrival Departure Surface (IADS) Scheduling

The objective of the NRA is to investigate and develop integrated scheduling solutions for arrival, departure and surface operations. The option year briefing summarizes simulation-based analyses of the departure metering process to investigate strategic queue management strategies and their robustness to uncertainty, assess the impact of delaying departures at their gates on blocking the arrivals destined for the same gates, and evaluate the effects and benefits of relaxing current-day MIT constraints when ATD-2 is in operation.

ATD-2↗

Effect of Uncertainty on Deterministic Runway Scheduling

Active runway scheduling involves scheduling departures for takeoffs and arrivals for runway crossing subject to numerous constraints. This paper evaluates the effect of uncertainty on a deterministic runway scheduler. The evaluation is done against a first-come- first-serve scheme. In particular, the sequence from a deterministic scheduler is frozen and the times adjusted to satisfy all separation criteria; this approach is tested against FCFS. The comparison is done for both system performance (throughput and system delay) and predictability, and varying levels of congestion are considered. The modeling of uncertainty is done in two ways: as equal uncertainty in availability at the runway as for all aircraft, and as increasing uncertainty for later aircraft. Results indicate that the deterministic approach consistently performs better than first-come-first-serve in both system performance and predictability.

Gupta, Gautam↗

Scheduling and Delivering Aircraft to Departure Fixes in the NY Metroplex with Controller-Managed Spacing Tools

In this paper, successful Time-Based Flow Management (TBFM) scheduling systems for arrivals are considered and adapted to apply to departures. We present a concept of operations that integrates Controller-Managed Spacing tools for departures (CMS-D) with existing tactical departure scheduling tools to coordinate demand at departure fixes in a metroplex environment. We tested our concept in a Human-in-the-Loop simulation and compared the effect of two scheduling conditions: 1) "Departure Scheduling" consisting of an emulation of the Integrated Departure and Arrival Capability (IDAC) where Towers and a Planner (Traffic Management Coordinator at the appropriate facility) coordinate aircraft scheduled takeoff times to departure fixes; and 2) "Arrival Sensitive Departure Scheduling" where, in addition, the Tower and Planner also consider arrival Scheduled Time of Arrivals (STAs) at the airport's dependent runway. Results indicate little difference between the two scheduling conditions, but a large difference between the No Tools and the two scheduling conditions with CMS-D tools. The scheduling/CMS-D tools conditions markedly reduced heading, speed clearances, and workload for controllers who were merging flows at the departure fixes. In the tool conditions, departure controllers conditioned departures earlier rather than later when aircraft were tied near the departure fixes. In the scheduling/CMS-D tools conditions, departures crossed the departure fixes 50 seconds earlier and with an 8% error rate (consisting of time ahead or behind desired time of arrival) compared to a 19% error rate in the No Tool condition. Two exploratory runs showed that similar beneficial effects can be obtained only with the CMS-D tools without scheduling takeoff times, but at the cost of a somewhat higher workload for controllers, indicating the benefits of pre-departure scheduling of aircraft with minimal delays. Hence, we found that CMS-D tools were very beneficial in the metroplex environment we tested but that further research is needed to clarify the benefits of the various scheduling approaches.

terminal airspace↗

Airspace Technology Demonstration 2 (ATD-2) Technology Description Document (TDD)

This Technology Description Document (TDD) provides an overview of the technology for the Phase 1 Baseline Integrated Arrival, Departure, and Surface (IADS) prototype system of the National Aeronautics and Space Administration's (NASA) Airspace Technology Demonstration 2 (ATD-2) project, to be demonstrated beginning in 2017 at Charlotte Douglas International Airport (CLT). Development, integration, and field demonstration of relevant technologies of the IADS system directly address recommendations made by the Next Generation Air Transportation System (NextGen) Integration Working Group (NIWG) on Surface and Data Sharing and the Surface Collaborative Decision Making (Surface CDM) concept of operations developed jointly by the Federal Aviation Administration (FAA) and aviation industry partners. NASA is developing the IADS traffic management system under the ATD-2 project in coordination with the FAA, flight operators, CLT airport, and the National Air Traffic Controllers Association (NATCA). The primary goal of ATD-2 is to improve the predictability and 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 project is a 5-year research activity beginning in 2015 and extending through 2020. The Phase 1 Baseline IADS capability resulting from the ATD-2 research will be demonstrated at the CLT airport beginning in 2017. Phase 1 will provide the initial demonstration of the integrated system with strategic and tactical scheduling, tactical departure scheduling to an en route meter point, and an early implementation prototype of a Terminal Flight Data Manager (TFDM) Electronic Flight Data (EFD) system. The strategic surface scheduling element of the capability is consistent with the Surface CDM Concept of Operations published in 2014 by the FAA Surface Operations Directorate.

integrated arrival↗