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NASA NTRS2019

Scheduling Improvements Following the Phase 1 Field Evaluation of the ATD-2 Integrated Arrival, Departure, and Surface Concept

NASA is conducting the Airspace Technology Demonstration-2 to evaluate an Integrated Arrival, Departure, and Surface (IADS) traffic management system that extends traffic sequencing for the entire life-cycle of a flight from departure gate to arrival gate within multi-airport, metroplex environments. After development and testing in human-in-the-loop simulations, the IADS system was deployed to Charlotte Douglas International Airport for a three-year field evaluation. From the initial IADS concept development through the end of the Phase 1 field evaluation many lessons were learned with regards to the IADS scheduler. In this paper we describe how data from the Phase 1 field evaluation helped identify scheduler improvements and guided the implementation of refinements. The improvements in the IADS scheduler described in this paper are incorporated into the IADS Phase 2 scheduler enabling strategic Surface Metering Programs and will be evaluated during the field evaluation.

Coupe, William J.↗
NASA NTRS2011

Automated scheduling for NASA’s Deep Space Network

This paper describes the DSN Scheduling Engine (DSE) component of a new scheduling system being deployed for NASA’s Deep Space Network. The DSE provides core automation functionality for scheduling the network, including the interpretation of scheduling requirements expressed by users, their elaboration into tracking passes, and resolving conflicts and constraint violations. The DSE incorporates both systematic search and repair-based algorithms, used for different phases and purposes in the overall system. It has been integrated in with a web application which provides its functionality to all DSN users through a standard web browser. The system is in the process of deployment to operational status.

Tran, Daniel↗
NASA NTRS2017

A Hybrid Traveling Salesman Problem - Squeaky Wheel Optimization Planner for Earth Observational Scheduling

We outline a hybrid planner for scheduling Observa- tion Requests on an Earth observing satellite, subject to a variety of constraints for the ASPEN (Chien et al. 2000) Eagle Eye adaptation (Knight, Donnellan, and Green 2013) that combines Squeaky Wheel Optimiza- tion (Joslin and Clements 1999) with sliding observa- tion planning (Aldinger et al. 2013). The Earth Ob- serving Satellite (EOS) planning problem (Globus et al. 2004) is reformulated as time-varying travel time TSP with interval constraints (Ichoua, Gendreau, and Potvin 2003). The replanning/ ll stage of the hybrid scheduler marginally improves schedule quality for all bus agilities examined, but has more impact on lower agility observers. The squeaky wheel stage primarily a ects overall schedule quality by satisfying high pri- ority requests, while the replanner reduces starvation of lower value requests.

Trowbridge, Michael↗
NASA NTRS2020

Onboard Automated Scheduling for the Mars 2020 Rover

The Mars 2020 Mission, scheduled to land on Mars February 18, 2021, has developed an onboard scheduling system [1]. The rationale for the onboard scheduler is to enable the Perseverance rover to adjust its activities in response to activities taking longer or shorter than planned, or using more or less resources than expected, as effectively using these resources could significantly improve rover productivity [2]. If deployed, the onboard scheduler would be an unprecedented use of Artificial Intelligence/Autonomy onboard software in a key role for a major mission.

Biehl, J.↗
NASA NTRS2020

Scheduling NASA's Deep Space Network: Priorities, Preferences, and Optimization

NASA's Deep Space Network (DSN) is the primary resource for communications and navigation for interplanetary space missions, for both NASA and partner agencies. Growth in mission demand, both in number of spacecraft and in data return, has led to increased loading levels on the network, and actual demand frequently exceeds network capacity. The DSN scheduling process involves peer-to-peer collaborative negotiation, which consumes significant time and resources in order to reach a baseline version of the schedule, and then to manage and agree to changes. Process delays are exacerbated by the high level of oversubscription experienced by the DSN: it is not unusual for the scheduling process to start with 20-40\% more requested time can be accommodated on the available antennas. The other NASA networks make use of a static mission priority list to address a similar problem: missions are ranked in priority order, then the schedule is populated by priority from highest to lowest. Such a mechanism would not work for DSN due to the heterogeneity of the mission set, and to the time-varying mission requirements with mission phase. This paper describes an alternative approach for the DSN that addresses key problems inherent in the current process --- oversubsubscription and how to "fairly'" reduce it to a manageable level. The main characteristics of the new approach are the use of loading-based limits based on balancing requested time, along with priorities and user preferences as the basis for optimization criteria that can be used by new algorithms.

Johnston, Mark D↗
NASA NTRS2020

Scheduling the Mapping of a planet under geometrical constraints

Scheduling the coverage of a planet by scientific instruments on board spacecrafts under observational constraints is central in a significant number of current and future missions for the exploration of the solar system. In this paper, we describe the components and algorithms of a software used to study early-phase mission design or to schedule daily operations of currently in-flight spacecraft. The scheduling problem at hand is usually a large combinatorial problem. A discretization process is described and several ordering algorithms are designed and compared. Experiments show that high-quality schedules can be produced by approaches combining reasoning about rolling, coverage and priorities.

Wells, Christopher↗
NASA NTRS2021

User Preference Optimization for Oversubscribed Scheduling of NASA’s Deep Space Network

NASA’s Deep Space Network (DSN) is the primary resource for communications and navigation for interplanetary space missions, for both NASA and partner agencies. Growth in mission demand, both in number of spacecraft and in data return, has led to increased loading levels on the network, and actual demand frequently exceeds network capacity. The DSN scheduling process involves peer-to-peer collaborative negotiation, which consumes significant time and resources in order to reach a baseline version of the schedule, and then to manage and agree to changes. Process delays are exacerbated by the high level of oversubscription experienced by the DSN: it is not unusual for the scheduling process to start with 20-40% more requested time can be accommodated on the available antennas. The other NASA networks make use of a static mission priority list to address a similar problem: missions are ranked in priority order, then the schedule is populated by priority from highest to lowest. Such a mechanism would not work for DSN due to the heterogeneity of the mission set, and to the time-varying mission requirements with mission phase. This paper describes an alternative approach for the DSN that addresses key problems inherent in the current process — oversubsubscription and how to “fairly” reduce it to a manageable level. The main characteristics of the new approach are the use of loading-based limits based on balancing requested time, along with priorities and user preferences as the basis for optimization criteria that can be used by new algorithms.

Johnston, Mark D↗
NASA NTRSDate not supplied

NICS (NASA Instrument Capabilities Study) Instrument Schedule and Cost Study

This paper summarizes work performed on the Flight Projects Directorate Planetary Science Projects Division (PSPD, Code 430) NICS (NASA Instrument Capabilities study) instrument schedule and cost study. Included are a short summary of the original NICS (NASA, 2008), and the design and approach, data collection, analysis, preliminary findings and recommendations from select areas of the current study. The NICS (2008) was chartered by then NASA Chief Engineer Michael Ryschkewitsch and chaired by Goddard Space Flight Center (GSFC) engineer, John Leon. The focus was to identify problem areas in instrument development and, if possible, to offer solutions. In the area of instrument developments, the NICS (2008) identified a lack of resources and authority to successfully manage to instrument cost and schedule requirements; and a lack of critical skills, expertise, and leadership to successfully implement unique (one-of-a-kind) high technology developments (NASA, 2008, pp. 51, 52). Additionally, the NICS (2008) found problems in requirements formulation, reviews and management; unrealistic caps and overly optimistic estimates; and externally directed changes which increased the likelihood of overrunning cost and schedule (NASA, 2008, pp.53, 54). It is noteworthy that NICS findings are consistent with previous studies at the mission level (Robbins, Schmidt & White, 2020). Five years later in 2013, the Instrument Projects Division (IPD) was established to implement and manage instrument projects greater than $20M. The IPD was known as Code 490. Its structure incorporated several of the NICS (2008) recommendations. To see if these incorporated recommendations made a difference, and to identify other potential challenges in instrument developments, two parallel studies were initiated. Originally led by the IPD, now led by the PSPD, and the Instrument and Payload Systems Engineering Branch (IPSE, Code 592), respectively, the instrument schedule and cost study and the instrument technical complexity study began in 2017. Data collection was initiated in 2020 and is on-going. This paper is limited to the IPD/PSPD study. Among other findings, preliminary data indicate IPD/PSPD project management support positively influenced instrument development as related to providing a dedicated level of support staff, including a deputy Instrument Project Manager (dIPM), reducing IPM leadership changes, and providing other project support. Next steps include continued data collection and analysis, and mapping to technical complexity data.

NICS implementation↗
NASA NTRS2019

Lessons Learned from International Space Station Crew Autonomous Scheduling Test

In 2017, our team investigated and evaluated the novel concept of operations of astronaut self-scheduling (rescheduling their own timeline without creating violations) onboard International Space Station (ISS). Five test sessions were completed for this technology demonstration called Crew Autonomous Scheduling Test (CAST). For the first time in a spaceflight operational environment, an ISS crewmember planned, rescheduled, and executed their activities in real-time on a mobile device while abiding by flight and scheduling constraints. This paper discusses the lessons learned from deployment to execution.

planning and scheduling↗
NASA NTRS2006

Collaborative Scheduling Using JMS in a Mixed Java and .NET Environment

A viewgraph presentation to demonstrate collaborative scheduling using Java Message Service (JMS) in a mixed Java and .Net environment is given. The topics include: 1) NASA Deep Space Network scheduling; 2) Collaborative scheduling concept; 3) Distributed computing environment; 4) Platform concerns in a distributed environment; 5) Messaging and data synchronization; and 6) The prototype.

.NET↗
NASA NTRS2007

Deep Space Network Scheduling Using Evolutionary Computational Methods

The paper presents the specific approach taken to formulate the problem in terms of gene encoding, fitness function, and genetic operations. The genome is encoded such that a subset of the scheduling constraints is automatically satisfied. Several fitness functions are formulated to emphasize different aspects of the scheduling problem. The optimal solutions of the different fitness functions demonstrate the trade-off of the scheduling problem and provide insight into a conflict resolution process.

Deep Space Network (DSN)↗
NASA NTRS2014

Calculation of Flight Deck Interval Management Assigned Spacing Goals Subject to Multiple Scheduling Constraints

The Federal Aviation Administration's Next Generation Air Transportation System will combine advanced air traffic management technologies, performance-based procedures, and state-of-the-art avionics to maintain efficient operations throughout the entire arrival phase of flight. Flight deck Interval Management (FIM) operations are expected to use sophisticated airborne spacing capabilities to meet precise in-trail spacing from top-of-descent to touchdown. Recent human-in-the-loop simulations by the National Aeronautics and Space Administration have found that selection of the assigned spacing goal using the runway schedule can lead to premature interruptions of the FIM operation during periods of high traffic demand. This study compares three methods for calculating the assigned spacing goal for a FIM operation that is also subject to time-based metering constraints. The particular paradigms investigated include: one based upon the desired runway spacing interval, one based upon the desired meter fix spacing interval, and a composite method that combines both intervals. These three paradigms are evaluated for the primary arrival procedures to Phoenix Sky Harbor International Airport using the entire set of Rapid Update Cycle wind forecasts from 2011. For typical meter fix and runway spacing intervals, the runway- and meter fix-based paradigms exhibit moderate FIM interruption rates due to their inability to consider multiple metering constraints. The addition of larger separation buffers decreases the FIM interruption rate but also significantly reduces the achievable runway throughput. The composite paradigm causes no FIM interruptions, and maintains higher runway throughput more often than the other paradigms. A key implication of the results with respect to time-based metering is that FIM operations using a single assigned spacing goal will not allow reduction of the arrival schedule's excess spacing buffer. Alternative solutions for conducting the FIM operation in a manner more compatible with the arrival schedule are discussed in detail.

ATD-1↗
NASA NTRS2013

Experiments with a Parallel Multi-Objective Evolutionary Algorithm for Scheduling

Evolutionary multi-objective algorithms have great potential for scheduling in those situations where tradeoffs among competing objectives represent a key requirement. One challenge, however, is runtime performance, as a consequence of evolving not just a single schedule, but an entire population, while attempting to sample the Pareto frontier as accurately and uniformly as possible. The growing availability of multi-core processors in end user workstations, and even laptops, has raised the question of the extent to which such hardware can be used to speed up evolutionary algorithms. In this paper we report on early experiments in parallelizing a Generalized Differential Evolution (GDE) algorithm for scheduling long-range activities on NASA's Deep Space Network. Initial results show that significant speedups can be achieved, but that performance does not necessarily improve as more cores are utilized. We describe our preliminary results and some initial suggestions from parallelizing the GDE algorithm. Directions for future work are outlined.

scheduling↗
NASA NTRS2014

Precision Arrival Scheduling for Tactical Reconfiguration

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

airport reconfiguration↗
NASA NTRS2019

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 NTRSDate not supplied

Capacity and Throughput of Urban Air Mobility Vertiports with a First-Come, First-Served Vertiport Scheduling Algorithm

In this paper, a first-come, first-served vertiport scheduling algorithm for Urban Air Mobility (UAM) was exercised to assess and compare the capacity and throughput of various vertiport configurations. The scheduler models each vertiport by the number of vertipads and parking spaces, and manages reservations on timelines for those vertiport resources, at a level of fidelity suitable for fast-time and system-level analyses of UAM concepts and other airspace studies. The paper defines the theoretical model that can be used to estimate the capacity of various vertiport configurations. The theoretical model provides an understanding of the conditions that can lead to either a parking space-limited or a vertipad-limited vertiport. Examples of potential throughput for some vertiport configurations are provided using both a queueing approach as well as a simulated UAM demand scenario. The study demonstrated that a first-come, first-served scheduling approach can have inefficiencies in the use of the vertiport resources. The inefficiencies can increase as the number of resources increases. Nonetheless, 80% or better peak throughput to capacity ratio was observed for most vertiport configurations.

UAM↗
NASA NTRS1997

Resource Scheduling for a Network of Communications Antennas

This paper describes tha Demand Access Network Scheduler (DANS) system for automatically scheduling and rescheduling resources for a network of communication antennas. DANS accepts a baseline schedule and supports rescheduling of antenna and subsystem resources to satisfy tracking goals in the event of changing track requests, equipment outages, and inclement weather.

Deep↗
NASA NTRS2021

Simulation Study for Interoperability of Urban Air Mobility Scheduling and Separation Services in Ideal Conditions

Provision of strategic scheduling and tactical separation services is vital to the safe and efficient operation of vehicles in the urban airspace. This paper describes the efforts made towards the integration of two such services in a simulation environment under ideal conditions and the subsequent studies done on evaluation of system performance. The scheduling and separation services are set up to complement each other to ensure safe separation between airborne aircraft. The utility of these services will become important as the level of traffic increases. This paper describes the simulation experiments conducted to identify cases where the system performance measured by the number of observed losses of separation degrades even with the scheduling and separation services active. From the results obtained, we identify conditions under which the required maneuvers increase and when we observe airborne conflicts even with separation service active. Results obtained will inform requirements for future advancements both in these services independently and in their joint operations.

Urban Air Mobility↗