In recent years, NASA has initiated the development of a focused near-to mid-term concept called "Integrated Demand Management" (IDM) under the Airspace Operations and Safety Program (AOSP). The focus of the research has been to develop more powerful, integrated operations and tools for managing trajectory constraints, leveraging existing systems and adding new automation tools and methods where needed. The IDM concept is predicated on the idea that in situations where the capacity of critical resources (such as airspace or airports) is insufficient to meet demand, a better match between available capacity and the predicted demand would significantly benefit the operations, with potential improvements in throughput, delays, and efficient flight trajectories. In current operations the reasons for the capacity/demand mismatches can vary, and range from problems due to structural limitations (e.g., surface capacity at high-volume airports, high-complexity en route or arrival airspace); to wind-related capacity changes; to the more severe, unstable and dynamic mismatches that occur with convective weather. The IDM solution proposes to address the demand / capacity mismatches by using the strategic flow management capabilities within the traffic flow management system (TFMS) toolset to "pre-condition" demand into the more tactical time-based flow management (TBFM) system, which should enable TBFM to better manage delivery to the capacity-constrained resource(s). The intent of IDM is to leverage the strengths of each of these systems to produce an integrated solution that is more powerful and robust than either could provide alone, or than the two would provide today as uncoordinated systems.Newark Liberty International Airport (EWR) was chosen to be the focus of our initial design problem for several reasons. EWR routinely sees scheduled demand at or near airport capacity through much of the day with a varying mix of short-haul and long-haul flights. Although this is usually managed effectively using miles-in-trail and TBFM metering, close-in departures can experience excessive and unpredictable ground delay if the overhead flow is saturated. In the initial development of IDM concept, an alternative solution to this volume problem was proposed that integrates 3 key capabilities: 1) Collaborative Trajectory Options Program (CTOP) capability within TFMS to issue traffic management initiatives that can "strategically" manage demand into the TBFM system; 2) TBFM capability closer to the destination airport to "tactically" manage delivery to the capacity-constrained destination; and 3) required-time-of-arrival (RTA) capability on the flight deck to provide a more controlled traffic demand using the CTOP derived schedule into the TBFM domain.The IDM concept development is ongoing and iterative, based on inputs from the FAA and airline stakeholders, as well as on insights gained from a series of human-in-the-loop

This paper introduces NASA's Integrated Demand Management (IDM) concept and presents the results from an early proof-of-concept evaluation and an exploratory experiment. The initial development of the IDM concept was focused on integrating two systems-i.e. the FAA's newly deployed Traffic Flow Management System (TFMS) tool called the Collaborative Trajectory Options Program (CTOP) and the Time-Based Flow Management (TBFM) system with Extended Metering (XM) capabilities-to manage projected heavy traffic demand into a capacity-constrained airport. A human-in-the-loop (HITL) simulation experiment was conducted to demonstrate the feasibility of the initial IDM concept by adapting it to an arrival traffic problem at Newark Liberty International Airport (EWR) during clear weather conditions. In this study, the CTOP was utilized to strategically plan the arrival traffic demand by controlling takeoff times of both short-and long-haul flights (long-hauls specify aircraft outside TBFM regions and short-hauls specify aircraft within TBFM regions) in a way that results in equitable delays among the groups. Such strategic planning decreases airborne and ground delay within TBFM by delivering manageable long-haul traffic demand while reserving sufficient slots in the overhead streams for the short-haul departures. A manageable traffic demand ensures the TBFM scheduler does not assign more airborne delay than a particular airspace is capable of absorbing. TBFM uses its time-based metering capabilities to deliver the desirable throughput by tactically coordinating and scheduling the long-haul flights and short-haul departures. Additional research was performed to explore the use of Required Time of Arrival (RTA) capabilities as a potential control mechanism to improve the arrival time accuracy of scheduled long-haul traffic. Results indicated that both short-and long-haul flights received similar ground delays. In addition, there was a noticeable reduction in the total amount of excessive, unanticipated ground delays, i.e. delays that are frequently imposed on the shorthaul flight in current day operations due to saturation in the overhead stream, commonly referred to as 'double penalty.' Furthermore, the concept achieved the target throughput while minimizing the expected cost associated with overall delays in arrival traffic. Assessment of the RTA capabilities showed that there was indeed improvement of the scheduled entry times into TBFM regions by using RTA capabilities. However, with respect to reduction in delays incurred within TBFM, there was no observable benefit of improving the precision of entry times for long-haul flights.

the objective of this study is to explore the use of Required Time of Arrival (RTA) capability on the flight deck as a control mechanism on arrival traffic management to improve traffic delivery accuracy by mitigating the effect of traffic demand uncertainty. The uncertainties are caused by various factors, such as departure error due to the difference between scheduled departure and the actual take-off time. A simulation study was conducted using the Multi Aircraft Control System (MACS) software, a comprehensive research platform developed in the Airspace Operations Laboratory (AOL) at NASA Ames Research Center. The Crossing Time (CT) performance (i.e. the difference between target crossing time and actual crossing time) of the RTA for uncertainty mitigation during cruise phase was evaluated under the influence of varying two main factors: wind severity (heavy wind vs. mild wind), and wind error (1 hour, 2 hours, and 5 hours wind forecast errors). To examine the CT performance improvement made by the RTA, the comparison to the CT of the aircraft that were not assigned with RTA (Non-RTA) under the influence of the selected factors was also made. The Newark Liberty International Airport (EWR) was chosen for this study. A total 66 inbound traffic to the EWR (34 of them were airborne when the simulation was initiated, 32 were predepartures at that time) was simulated, where the pre-scripted departure error was assigned to each pre-departure (61 % conform to their Expected Departure Clearance Time, which is +/-300 seconds of their scheduled departure time). The results of the study show that the delivery accuracy improvement can be achieved by assigning RTA, regardless of the influence of the selected two factors (the wind severity and the wind information inaccuracy). Across all wind variances, 66.9% (265 out of 396) of the CT performance of the RTA assigned aircraft was within +/-60 seconds (i.e. target tolerance range) and 88.9% (352 out of 396) aircraft met +/-300 seconds marginal tolerance range, while only 33.6% (133 out of 396) of the Non-RTA assigned aircraft's CT performance achieved the target tolerance range and 75.5% (299 out of 396) stayed within the marginal. Examination of the impact of different error sources -i.e. departure error, wind severity, and wind error -suggest that although large departure errors can significantly impact the CT performance, the impacts of wind severity and errors were modest relative the targeted +/-60 second conformance range.

Air traffic management in the New York (NY) metropolitan area presents significant challenges including excess demand, chronic delays, and inefficient routes. At NASA, a new research effort has been initiated to explore Next Generation Air Transportation System (NextGen) Trajectory Based Operations (TBO) solutions to address lingering problems in the NY metroplex. One of the larger problems in NY is departure delays at LaGuardia airport (LGA). Constant traffic demand and physical limitations in the number of taxiways and runways cause LGA to often end up with excessive departure queues that can persist throughout the day. At the Airspace Operations Laboratory (AOL) located at NASA Ames Research Center, a TBO solution for "Departure-Sensitive Arrival Spacing" (DSAS) was developed. DSAS allows for maximum departure throughput without adversely impacting the arrival traffic during the peak demand period. The concept uses Terminal Sequencing and Spacing (TSS) operations to manage the actual runway threshold times for arrivals. An interface enhancement to the traffic manager's timeline was also added, providing the ability to manually adjust inter-arrival spacing to build precise gaps for two or even three departures between arrivals. With this set of capabilities, inter-arrival spacing could be controlled for optimal departure throughput. The concept was prototyped in a human-in-the-loop (HITL) simulation environment to determine operational requirements such as coordination procedures, timing and magnitude of TSS schedule adjustments, and display features for the tower, Terminal Radar Approach Control (TRACON), and Traffic Management Unit (TMU). A HITL simulation was conducted in August, 2014, to evaluate the concept in terms of feasibility, impact on controller workload, and potential benefits. Three conditions were compared: (1) a baseline condition using new RNAV/RNP procedures (no TSS); (2) the new procedures + TSS; and (3) new procedures + TSS + DSAS schedule adjustments. Results showed that with a maximum arrival demand (40-41 arrivals per hour), departure throughput could be increased from 38 / hour (baseline condition), to 44 / hour (TSS condition), to 47 / hour (TSS + DSAS). The results suggest that DSAS operations have the potential to increase departure throughput at LGA by up to 9 a/c per hour with little or no impact on arrivals during peak traffic demand period.

A human-in-the-loop evaluation of the Operational Airspace Sectorization Integrated System (OASIS) was conducted in the Airspace Operations Laboratory at NASA Ames Research Center. OASIS is an advisory tool built on an Android touch tablet, designed to assist Federal Aviation Administration (FAA) En Route Area Supervisors in their planning of sector combine/split operations as well as opening/closing of radar associate control positions over the subsequent two hours. During the experiment, eight retired FAA personnel served as participants for a part-task evaluation of the OASIS user interface and the underlying mathematical algorithm that provided the advisories. There were three experimental conditions: Baseline, Computer Recommend Plan (CRP), and User Generated Plan (UGP). In the Baseline condition, participants were presented with four different traffic scenarios and were asked to generate their own sector configuration plan solutions without OASIS. In the CRP condition, they evaluated the multiple advisory solutions that were generated by OASIS. In the UGP condition, they modified the OASIS advisory solutions to make their own solutions with the support of the OASIS tool. The participants considered the OASIS advisory solutions at least as good as their own, suggesting that the underlying algorithm provided good solutions for the Area Supervisors. In the UGP condition, the participants could not improve on the OASIS advisories by further tweaking the solutions. Participants gave positive feedback on both the user interface and the algorithm solutions, including an excellent average rating above 90% on the tool usability scales. They also suggested various enhancements to be incorporated into the next tool development cycle. The development of OASIS is a major activity of the Dynamic Airspace Configuration (DAC) research focus area within the Airspace Systems Program.

This paper presents the methodology and results of a Human-In-The-Loop (HITL) simulation study conducted in the Airspace Operations Laboratory at NASA Ames Research Center. This study is a part of NASA's ongoing research into developing an Integrated Demand Management (IDM) concept, whose aim is to improve traffic flow management (TFM) by coordinating the FAA's strategic Traffic Flow Management System (TFMS) with its more tactical Time-Based Flow Management (TBFM) system. The purpose of TFM is to regulate air traffic demand so that it is delivered efficiently through constrained airspace resources without exceeding their capacity limits. The IDM concept leverages a new TFMS capability called the Collaborative Trajectory Options Program (CTOP) to strategically precondition traffic demand flowing into a TBFM-managed arrival environment, where TBFM is responsible for managing traffic tactically by generating precise arrival schedules. Unlike other TFM tools, CTOP gives flight operators the option of submitting a set of user-preferred alternative trajectories for each flight. CTOP can then use these trajectory option sets (or TOSs) to find user-preferred alternative routes to reduce demand on an overloaded resource. CTOP's effectiveness in redistributing demand is limited, however, by the availability of flights with alternative routes. The research presented in this paper focuses on evaluating the impact on TFM operations by varying the percentage of flights that submit a multiple-option TOS ('TOS participation levels'). Results show the impact on overall system performance and on the rerouted flights themselves. The simulation used a Newark (EWR) airport arrival scenario, with en route weather affecting traffic inbound from the west. Participants were asked to control each of the three arrival flows (north, west, and south) to meet their individual capacity constraints while simultaneously ensuring efficient utilization of the capacity at the destination airport. A large, permeable convective weather cell located southeast of Chicago severely reduced the capacity of the west flow. The study evaluated the impact of five different TOS participation levels on CTOP's ability to re-allocate traffic from the west and improve TFM performance in terms of delay assignment and traffic delivery rate to the airport.Overall, the results showed that increasing TOS submissions allowed the overall system delays to be reduced and fairly distributed among the three arrival flows, at the same time achieving the airport throughput rate. Moreover, it was found that aircraft who submitted a TOS saw a greater reduction in delay, even when they were assigned longer routes. This was particularly true when fewer aircraft submitted a TOS. The results confirm that the CTOP operations

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NASA has initiated a NextGen Future Environments research effort to explore how TAPSS and other NASA efforts (e.g. efficient trajectory and flow planning, separation assurance, dynamic airspace configuration, and time-based metering) can be combined and adapted to improve operational performance in a particularly complex, high-demand airspace. The enabling NextGen technologies and https://ntrs.nasa.gov/search.jsp?R=20140010404 2020-07-16T16:58:21+00:00Z