Delay Sensitivity to Call For Release Scheduling Time

Since it is safer and less expensive to absorb delays on the ground, many models have been developed to assign ground holding delays optimally in the general network of airports, so that the total (ground plus airborne) delay costs of all fights are minimized. Still, the undeniable fact remains that airborne delays cannot be totally avoided. When there are airborne holds, such as when the local airspace capacity has a sudden decrease due to bad weather or other unpredicted disruptions, it is important to quickly minimize the costs of airborne holds. Much research has been conducted to explore ways to minimize airborne holds. Motivated by this, after analyzing the network structure of air traffic control areas and the dynamic nature of air traffic flow, this paper presents a model based on multicommodity dynamic network flow for short-term air traffic flow management. The model was validated by practical data from the Beijing ATC Center of the Civil Aviation Administration of China (CAAC).

NASA's Aeronautics Research Mission Directorate (ARMD) collaborates with the FAA and industry to provide concepts and technologies that enhance the transition to the next-generation air-traffic management system (NextGen). To facilitate this collaboration, ARMD has a series of Airspace Technology Demonstration (ATD) sub-projects that develop, demonstrate, and transitions NASA technologies and concepts for implementation in the National Airspace System (NAS). The second of these sub-projects, ATD-2, is focused on the potential benefits to NAS stakeholders of integrated arrival, departure, surface (IADS) operations. To determine the project objectives and assess the benefits of a potential solution, NASA surveyed NAS stakeholders to understand the existing issues in arrival, departure, and surface operations, and the perceived benefits of better integrating these operations. NASA surveyed a broad cross-section of stakeholders representing the airlines, airports, air-navigation service providers, and industry providers of NAS tools. The survey indicated that improving the predictability of flight times (schedules) could improve efficiency in arrival, departure, and surface operations. Stakeholders also mentioned the need for better strategic and tactical information on traffic constraints as well as better information sharing and a coupled collaborative planning process that allows stakeholders to coordinate IADS operations. To assess the impact of a potential solution, NASA sketched an initial departure scheduling concept and assessed its viability by surveying a select group of stakeholders for a second time. The objective of the departure scheduler was to enable flights to move continuously from gate to cruise with minimal interruption in a busy metroplex airspace environment using strategic and tactical scheduling enhanced by collaborative planning between airlines and service providers. The stakeholders agreed that this departure concept could improve schedule predictability and suggested several key attributes that were necessary to make the concept successful. The goals and objectives of the planned ATD-2 sub-project will incorporate the results of this stakeholder feedback.

In this paper we analyze alternative near-term Traffic Flow Management Operational Incentives (OPI). These OPIs are part of a larger effort to help accelerate airlines’ equipage efforts with respect to NextGen avionics in the areas of Communication, Navigation, and Surveillance. We analyze alternative operational incentives that can be implemented through the slot allocation process in a Ground Delay Program. Potential incentives can either provide natural benefits through capacity increase, or redistribute ground delays in a zero-sum fashion in favor of equipped flights. We argue that, due to the complex nature of airline operations, quantifying the benefits of these incentives can be challenging. Furthermore, as airlines compete for limited resources in the National Airspace System, incentives may trigger different actions among airlines. Thus we propose a marginal analysis with respect to varying equipage mixtures to study the local and system-wide ramifications of possible equipage decisions made by airlines in reaction to each incentive. This analysis framework can aid policymakers in selecting the appropriate operational incentive mechanisms to yield desirable outcomes. ull realization of NextGen benefits to the National Airspace System (NAS) relies upon aircraft being equipped with certain technological systems. However, the equipage process has faced impediments that have slowed equipage rates below targets. These impediments include high costs of acquisition, retrofitting, and crew training. Furthermore, uncertainty regarding return on investment in terms of the time until benefits start to accrue, as well as the actual magnitude of the benefits, complicates the decision-making process for the airlines to equip. Moreover, due to the highly competitive nature of airline operations, unresolved issues, such as early adopter versus free rider , exacerbate the uncertainty among airlines in making the decision to equip their fleets. It is believed that a combination of financial 1 and operational incentives 2,3 can help accelerate the equipage process by alleviating some uncertainty regarding the realization of the benefits associated with equipage. Previous studies 2,4 have indicated that strategic-level Traffic Management Initiatives (TMI) such as Ground Delay Programs (GDP) and Airspace Flow Programs (AFP) can be used as a vehicle for Traffic Flow Management (TFM) Operational Incentives (OPI). Such incentives can be implemented by changing the resource allocation algorithms used to assign ground delays to flights. These alterations affect the distribution of benefits—in the form of delay reductions—among equipped and unequipped flights. The Joint Planning and Development Office (JPDO) offers an in-depth analysis of resource allocation and flight prioritization mechanisms in TMIs. 5 We classify TFM OPIs into two major categories based on how benefits are generated. The first category of incentives is associated with transitional benefits, in which equipage may not result in a near-term increase in capacity or throughput. The second category of incentives is associated with natural benefits, wherein increased capacity or throughput arises from the equipage and the consequent improvement in the aircraft performance.

The expected growth in air travel demand and the positive correlation with the economic factors highlight the significant contribution of the aviation community to the U.S. economy. On‐time operations play a key role in airline performance and passenger satisfaction. Thus, an accurate investigation of the variables that cause delays is of major importance. The application of machine learning techniques in data mining has seen explosive growth in recent years and has garnered interest from a broadening variety of research domains including aviation. This study employed a support vector machine (SVM) model to explore the non-linear relationship between flight delay outcomes. Individual flight data were gathered from 20 days in 2018 to investigate causes and patterns of air traffic delay at three major New York City airports. Considering the black box characteristic of the SVM, a sensitivity analysis was performed to assess the relationship between dependent and explanatory variables. The impacts of various explanatory variables are examined in relation to delay, weather information, airport ground operation, demand-capacity, and flow management characteristics. The variable impact analysis reveals that factors such as pushback delay, taxi-out delay, ground delay program, and demand-capacity imbalance with the probabilities of 0.506, 0.478, 0.339, and 0.338, respectively, are significantly associated with flight departure delay. These findings provide insight for better understanding of the causes of departure delays and the impacts of various explanatory factors on flight delay patterns.

This paper documents the results of fast-time simulations evaluating potential capacity benefits of procedure concepts developed for parallel approaches to closely spaced parallel runways (CSPR) at airports with runway spacing less than 2,500 feet. Currently, simultaneous arrival operations at CSPR airports rely on visual meteorological conditions (VMC). In inclement weather when visual procedures can no longer be applied, simultaneous arrivals must be discontinued. Application of standard aircraft separations based on instrument flight rules (IFR) effectively results in the loss of arrival operations on one of the two runways, significantly reducing the arrival capacity of CSPR airports. Proposed wind-dependent parallel approach concepts promise improvements in arrival capacity at CSPR airports by enabling continued operations of dual arrival streams in instrument meteorological conditions (IMC). The concepts permit dependent parallel arrival operations when meteorological conditions are determined to render approach paths free of wake vortices from preceding aircraft. The operations are expected to increase capacity during IMC and decrease weather-related delays at CSPR airports. Simulation results for 9 CSPR airports in the National Airspace System (NAS) suggest significant potential capacity benefits ranging from 2 to 18 additional arrival operations per hour depending upon the concept and airport. The paper outlines the proposed wake independent straight-in parallel approach concept and 12 procedural derivatives. It describes the model developed to visualize the operations and the Monte Carlo approach taken to quantify potential capacity benefits.

Ground-holding policies (GHPs) in air traffic control aim at trading off unavoidable airborne delays for ground delays in order to prevent uncontrollable situations where a number of airplanes is placed in a "holding pattern" over busy destination airports. The fundamental issue in any GHP is to determine which flights should be delayed and for how long. We address the GHP and propose a finite perturbation analysis (FPA) technique that can be used to dynamically solve the problem. We show that our approach leads to a control algorithm that achieves a global optimum in the sense that it eliminates airborne delays. Numerical results are included based on data from Boston's Logan Airport.

The aviation industry faces the urgent challenge of reconciling projected traffic growth with stringent climate targets, including the European Union’s goal of climate neutrality by 2050. While techno-logical innovations such as sustainable aviation fuels and hydrogen propulsion are critical for long-term decarbonization, their near-term impact remains limited. In this thesis, we address the immediate opportunity of improving the environmental efficiency of aircraft arrival operations in Terminal Manoeuvring Areas (TMAs), where congestion and complex sequencing often lead to excess fuel burn, emissions and noise. Existing research has demonstrated the benefits of Continuous Descent Operations (CDOs) and structured arrival procedures such as Point Merge (PM). However, for TMA performance evaluations, cur-rent practices are limited in real-world assessments of environmental efficiency beyond Carbon Dioxide (CO2). In terms of optimization of the arrival operations, the exploration of dynamic PM usage and early speed adjustments as a sequencing tool, integrated within the optimization framework, remains relatively unexplored. Furthermore, most optimization frameworks do not fully integrate arrival and departure scheduling in mixed-mode runway environments. The thesis addresses four key research questions: (1) What are the environmental benefits of using fuel-efficient CDOs within TMA and how to quantify them? (2) How to evaluate the arrival aircraft performance within TMAs implementing PM procedures? (3) Can the performance of current operations in a TMA where PM is implemented be improved by using optimization? (4) How can speed adjustment during cruise and descent be used, with or without combining it with PM procedures, to safely separate and sequence arriving flights? The overarching aim is to develop methodologies for assessing and optimizing arrival operations to reduce fuel consumption, emissions and noise while maintaining safety and capacity. The research combines data-driven performance evaluation with mathematical optimization. We use real-world Automatic Dependent Surveillance Broadcast (ADS-B) trajectory data from the OpenSky Network, together with meteorological data from ECMWF ERA5 and the performance modeling capabilities of EUROCONTROL BADA, to quantify inefficiencies in current operations. For optimization, we develop a Mixed-Integer Programming (MIP)-based framework to assign conflict-free, fuel-efficient arrival routes and descent profiles, incorporating wake turbulence separation and runway scheduling constraints. We perform case studies at Dublin and Oslo-Gardermoen airports, both operating with PM procedures. Empirical analysis reveals substantial inefficiencies in current TMA operations, with level-flight segments contributing significantly to excess fuel burn. Our studies show that CDOs reduce fuel consumption and noise exposure, although Carbon Monoxide (CO) and Hydrocarbon (HC) emissions may increase under idle-thrust conditions. Optimization results demonstrate that dynamic PM usage and early speed adjustments improve horizontal and vertical efficiency, reduce time in TMA and decrease fuel burn compared to actual operations. Operational improvements in arrival management can deliver immediate environmental benefits, complementing long-term technological solutions. The proposed frameworks support SESAR and NextGen objectives for greener TMAs and are adaptable to future contexts, including Urban Air Mobility (UAM). By integrating rigorous performance evaluation with advanced optimization, this thesis provides actionable insights for reducing aviation’s environmental footprint while enhancing predictability.

Congested airspace causes flight delays, which result in extra fuel burn, extra CO2 emissions, and additional workload for air traffic controllers in charge. Unlike road vehicles, once airborne, aircraft cannot stop in the air and turn off their engines. When the airspace of the arrival airport is going to be congested, however, airport can be delayed before their takeoff at the departure airport. Such traffic flow control, often referred to as ground holding, has been implemented in many countries already, with Japan being no exception. Currently, when flights are expected to be delayed in the air for more than a certain time (called buffer here), the ground holding program assigns delayed departure times. If there are no uncertainties in departure time and flight time, the optimal buffer can be easily determined. In reality, however, late passengers, for instance, can delay the departure. This research considers the uncertainties in departure time and enroute flight time to determine the optimal buffer applied by the ground holding program. Adopting values used by other researchers, the authors evaluate the cost of ground delay, airborne delay, and the cost of lost capacity, to determine the total cost of delay which is used as the metric for determining the optimal buffer. Results from Monte Carlo simulations show that there exist an optimal buffer for each traffic flow queue, but robustness can be achieved by implementing a sub-optimal buffer depending on the overall congestion only. Directions for further study and discussions are also presented.

We present a fully-dynamic multi-commodity Network Flow Model (NetFM) representation of the National Airspace System (NAS). NetFM is a high-level aggregate model incorporating time-varying demand and capacity profiles to define the optimal routing and scheduling of all NAS traffic within a matter of minutes. NetFM routing solutions are not limited to a set of user-inputted route options. Rather, spatial-temporal flight paths are computed through a hexagonal network of nodes and arcs over successive time steps. We present the NetFM formulation. NetFM results include a set of diagnostics which show predicted capacity, traffic flow patterns, and regions where additional capacity would be most beneficial. These diagnostic results may offer improved situational awareness and decision support to Traffic Flow Management (TFM) planners. NetFM capabilities also enable a laboratory in which TFM researchers can study advanced TFM concepts such as integrated airspace flow and ground delay programs.

Methods for determining unimpeded aircraft taxiing time and evaluating airport taxiing performance

The focus of this paper is on the problem of airline schedule recovery when airspace capacity is limited by convective weather. The problem is represented in a simulation, the Boeing National Flow Model (NFM), and an analysis is conducted to measure the benefits of increased automation and improved weather forecasting. In particular, an analysis is undertaken based upon all scheduled traffic and the actual convective weather experienced on specific good and bad weather days for the U.S. National Airspace System (NAS) in the year 2007. The analysis quantifies the benefits associated with a collaborative flow management concept involving distributed airline schedule recovery. The concept permits airline users to optimize or re-plan their own schedules given an assigned and equitable share of forecast system capacities. The methodology can be used to evaluate alternative convective weather forecasting products, including both polygonal forecasts (such as the CCFP), along with gridded probabilistic forecasts. The methodology can also utilize the actual weather, typically available in snapshots every 5-6 minutes, as a gridded 0/1 “perfect” forecast. The analysis was conducted and is reported on in two major phases. In both phases of the study we allowed the use of strategies for ground delay and flight cancellation but did not allo w for re-routing. The first phase of the analysis was an initial attempt to study the relative value of alternative forecasts and levels of planner automation and utilized multiple forecasting products in their original form. In this phase, we discovered a systematic difference (i.e., bias) in overall coverage between the forecast and actual weather. The forecasts contained much higher levels of weather coverage, leading to re-planning responses that were considerably over-reactive. These findings led to a forecast calibration effort at NOAA that served to adjust both the forecast and actual weather coverage to greatly reduce or eliminate the bias. In the second phase of the study we undertook to compare multiple calibrated forecasting products as well as alternative levels of planner automation.

The aviation community worldwide has been working for sometime to define a vision of the future air transportation system. The overall progress thus far has been primarily at a conceptual stage. This paper integrates a number of operational concepts into a realizable vision for the National Airspace System (NAS). A process is defined to help develop future operational scenarios based on the makeup of year 2020 fleet mix and aircraft avionics capabilities, considering non-scheduled on-demand, charter, travel club, fractional and short-haul intra-city operations. A majority of aircraft are projected to be able to fly via 4D navigation and to assume a larger share of the responsibility for maintaining separation. This would require significant investment in avionics and the automation of the ground system and infrastructure. Cost/benefits analysis is a key portion of the process. Example results are presented to illustrate return on investment over time as more and more aircraft are equipped with enhanced avionics. The operational benefits of 4D navigation operations are derived from reduced air and ground delays determined from the NAS-wide simulation of future operations. The example presented compared the life cycle costs of air/ground enhancements as function of aircraft equipage to ascertain that the overall benefits outweigh the implementation costs over time. The process is based on a number of operational assumptions and likely air/ground system enhancements beyond the currently planned enhancements over next 10 years. The evaluation process presented in the paper can be used to help understand the benefits and limitations of the future operational concepts, and intends to help define an ideal, but realistic vision of the future air transportation system for guiding research cost effectively.

View Video Presentation: https://doi.org/10.2514/6.2022-3835.vid This paper investigates the theoretical feasibility of controlling arrival airborne delays by acting on ground delays at departure airports, with the aim to reduce CO2 emissions. One challenge lies in the decision making to trigger ground delays few hours in advance under uncertainties in airborne delays prediction and during flight execution. We performed a sensitivity analysis, considering a control of the average airborne delay per 30 minutes period, varying the target from 10 down to 2 minutes, and measuring airborne delays, ground delays and runway throughput. We developed a simulation model of the arrival flow management process with a simplified regulation mechanism to trigger ground delays and realistic uncertainties on off-block, take-off time and flight duration. We selected four European airports subject to significant airborne delays in 2019 and with a median flight duration of 2 hours. We considered standard days and extracted results of the peak periods with airborne delays exceeding 10 minutes in the simulated “today” scenario, for a total duration of 1,900 hours and with 60,000 flights. Simulation results show that airborne delays can be effectively controlled, until a 6 minutes or even a 4 minutes target, while the 2 minutes target is missed. With the 6 minutes target scenario, for the four airports (weighted average), the cumulated airborne delays decreases by 56% compared to the “today” scenario (from 7 hours down to 3 hours) leading to a reduction of 19 tons of CO2 per peak hour, with no apparent detrimental effect on the runway throughput. However, with the uncertainties and exempted flights, the average total delay (airborne + ground) increases by 10% (from 8 hours to 9 hours), and the 90th percentile of the ground delay per flight from 13 to 29 minutes. These trends confirm the interest to extend these investigations, in particular regarding the impact on the network, departure airports and airspace user’s operations.

The modernization of the nation's air transportation system is necessary to accommodate forecasted traffic growth while ensuring safety. The National Airspace System (NAS) capacity is constrained by airport arrival and departure rate limitations due to factors such as weather delays, airline schedule conflicts, and aging infrastructures. New technologies such as data link messaging between ground-based air traffic management systems, tower controllers and flight decks, controller surface decision support tools, and cockpit digital maps are being developed to meet airport capacity upgrade needs. The benefits sought by data link are to reduce the need for voice communications between the pilot and controller, lower the likelihood of pilot readback and controller hearback errors, which, in turn, should reduce operator workload. The benefits sought by the surface management tools are to provide more optimized taxi routes, taxi conformance monitoring, and departure scheduling; which, in turn, will increase take-off capacity while reducing fuel, noise and environmental impacts. The data link messages are planned to cover all aspects of the taxi-out and taxi-in operations. However, for safety reasons, tactical process steps (e.g. runway crossing clearances) will still be issued verbally by the controllers. Data link messages are planned to eventually become the predominant mode of communication between controllers and pilots, but will still be supplemented by voice-based instructions as well as the use of paper-based airport maps. The transition to data link operations will impact how pilots and controllers communicate and share common and synchronous situation awareness (SA). The user interface design and operational procedure requirements to ensure that the desired safety and efficiency benefits still need definition. The paper provides a summary of past research activities and highlights unresolved research issues related to the implementation of data link taxi messaging within an integrated air-ground surface traffic management system.1,2

The Ration by Schedule (RBS) algorithm has been accepted by the aviation community as the basis of Collaborative Decision Making (CDM) in strategic Traffic Flow Management (TFM) initiatives such as Ground Delay Programs (GDPs) and Airspace Flow Programs (AFPs). However, applications of RBS to date have been limited to strategic metering applications in which the slots to be allocated to flights are all of equal duration, and the flights to be assigned to slots do not need to be differentiated. Decision support capabilities for the general Air Traffic Management (ATM) problem require planning and scheduling algorithms that properly recognize different flight characteristics such as weight class, runway, departure direction and other Air Traffic Control (ATC) procedural issues in determining the slot size that is required for each flight. In this paper, we describe our design and implementation of the Generalized RBS algorithm for a surface traffic management scheduling application which involves detailed flight-by-flight slot time assignment. This algorithm has been designed and developed to support the Collaborative Departure Queue Management (CDQM) component of the Surface Trajectory Based Operations (STBO) project. CDQM provides an equitable allocation of departure capacity to each flight operator at an airport for dynamic use in management of departure queues. The principles of the RBS algorithm are achieved through an initial planning pass based on scheduled data, followed by a second planning pass in which dynamic flight status is incorporated into the planning results.