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Analyzing the effectiveness of rescheduling and Flexible Execution methods to address uncertainty in execution duration for a planetary rover
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Application of Hybrid Optimization-Expert System for Optimal Power Management on Board Space Power Station
The space power system has two sources of energy: photo-voltaic blankets and batteries. The optimal power management problem on-board has two broad operations: off-line power scheduling to determine the load allocation schedule of the next several hours based on the forecast of load and solar power availability. The nature of this study puts less emphasis on speed requirement for computation and more importance on the optimality of the solution. The second category problem, on-line power rescheduling, is needed in the event of occurrence of a contingency to optimally reschedule the loads to minimize the 'unused' or 'wasted' energy while keeping the priority on certain type of load and minimum disturbance of the original optimal schedule determined in the first-stage off-line study. The computational performance of the on-line 'rescheduler' is an important criterion and plays a critical role in the selection of the appropriate tool. The Howard University Center for Energy Systems and Control has developed a hybrid optimization-expert systems based power management program. The pre-scheduler has been developed using a non-linear multi-objective optimization technique called the Outer Approximation method and implemented using the General Algebraic Modeling System (GAMS). The optimization model has the capability of dealing with multiple conflicting objectives viz. maximizing energy utilization, minimizing the variation of load over a day, etc. and incorporates several complex interaction between the loads in a space system. The rescheduling is performed using an expert system developed in PROLOG which utilizes a rule-base for reallocation of the loads in an emergency condition viz. shortage of power due to solar array failure, increase of base load, addition of new activity, repetition of old activity etc. Both the modules handle decision making on battery charging and discharging and allocation of loads over a time-horizon of a day divided into intervals of 10 minutes. The models have been extensively tested using a case study for the Space Station Freedom and the results for the case study will be presented. Several future enhancements of the pre-scheduler and the 'rescheduler' have been outlined which include graphic analyzer for the on-line module, incorporating probabilistic considerations, including spatial location of the loads and the connectivity using a direct current (DC) load flow model.
A space station onboard scheduling assistant
One of the goals for the Space Station is to achieve greater autonomy, and have less reliance on ground commanding than previous space missions. This means that the crew will have to take an active role in scheduling and rescheduling their activities onboard, perhaps working from preliminary schedules generated on the ground. Scheduling is a time intensive task, whether performed manually or automatically, so the best approach to solving onboard scheduling problems may involve crew members working with an interactive software scheduling package. A project is described which investigates a system that uses knowledge based techniques for the rescheduling of experiments within the Materials Technology Laboratory of the Space Station. Particular attention is paid to: (1) methods for rapid response rescheduling to accommodate unplanned changes in resource availability, (2) the nature of the interface to the crew, (3) the representation of the many types of data within the knowledge base, and (4) the possibility of applying rule-based and constraint-based reasoning methods to onboard activity scheduling.
Automatic generation of efficient orderings of events for scheduling applications
In scheduling a set of tasks, it is often not known with certainty how long a given event will take. We call this duration uncertainty. Duration uncertainty is a primary obstacle to the successful completion of a schedule. If a duration of one task is longer than expected, the remaining tasks are delayed. The delay may result in the abandonment of the schedule itself, a phenomenon known as schedule breakage. One response to schedule breakage is on-line, dynamic rescheduling. A more recent alternative is called proactive rescheduling. This method uses statistical data about the durations of events in order to anticipate the locations in the schedule where breakage is likely prior to the execution of the schedule. It generates alternative schedules at such sensitive points, which can be then applied by the scheduler at execution time, without the delay incurred by dynamic rescheduling. This paper proposes a technique for making proactive error management more effective. The technique is based on applying a similarity-based method of clustering to the problem of identifying similar events in a set of events.
Airspace Technology Demonstration 2 (ATD-2): Analysis of APREQ Flights at CLT
5/22/2019 National Aeronautics and Space Administration 1 Airspace Technology Demonstration 2 (ATD-2) Analysis of APREQ Flights at CLT May 22, 2019 5/22/2019 Objective 2 Quantify impact of IADS Phase 1 & 2 capabilities on APREQ flights at CLT with respect to: • Compliance to the Controlled Take Off Time (CTOT) • Benefits for APREQ flights that use IDAC to renegotiate for an earlier CTOT • Benefits of pre-scheduling APREQ flights using the Earliest Off Block Time (EOBT) • Relationship between EOBT compliance and rescheduling CTOT 5/22/2019 CLT APREQ Daily Compliance(Compliance Improvement Since ATD-2 Start) 3 Steady increase of APREQ compliance over the life of the project. Reduced variation in compliance leading to improved predictability. In addition to overall improved compliance into TBM systems, the predictability is increasing 5/22/2019 APREQ Compliance 10K Rolling Window 4 The most substantial APREQ compliance improvements started with Phase 2 capability (AEFS integration, ZTL IDAC, pre-scheduling and scheduler updates). 5/22/2019 IADS Phase 1 & 2 Benefit Mechanisms 5 1. Collaborative surface metering •Reduced engine run time •Reduced fuel consumption and emissions 2. Overhead stream operational integration a.Scheduling controlled flights at the gate •Reduced engine run time •Reduced fuel consumption and emissions b.APREQ renegotiating for an earlier slot •Reduced total delay •Passenger value of time and crew costs •Reduced engine run time •Reduced fuel consumption and emissions Benefits (1) and (2a) achieved through tactical gate holds Benefit (2b) achieved through APREQ renegotiation process described below Step 1: APREQ flight has a release time but is capable of taking off earlier Step 2: FAA TMC uses the IDAC green space / red space to identify and request an earlierslot in the overhead stream Step 3: Aircraft receives earlierrelease time and the difference between the release times is the reduction in delay 5/22/2019 Benefits for APREQ flights using IDAC to renegotiate for earlierCTOT 6 LBS Fuel 270.7 hours of delay saved by electronically renegotiating a better overhead stream time for 2,071 flights. • The benefits described here are associated with better use of existing capacity in the overhead stream, and technology to reduce surface delay. •These benefits are in addition to (distinct from) surface metering savings. 5/22/2019 APREQ Delay For Pre-Scheduled Flights into KATL Have Been Reduced and are More Predictable For the Last Five Months 7 Substantial Improvements in predictability of delay for the last 5 months 5/22/2019 EOBT Compliance / CTOT Reschedulefor Pre-Scheduled Flights into KATL 8 5/22/2019 Wrap-up 9 • Compliance to the CTOT has improved throughout the lifecycle of ATD-2 with biggest improvements following the introduction of Phase 2 capabilities • Rescheduling APREQ flights using IDAC has reduced 270.7 hours of delay at CLT • Predictability of local surface delay for APREQ flights is substantially improved via pre-scheduling with the IADS system • Pre-scheduled flights that reschedule for later times tend to call ready later with respect to EOBT
Towards a Characterization of Scheduling Task Complexity
Future long-duration missions will require astronauts to act more autonomously, manage their schedules, and replan timelines as anomalies and discoveries occur. Astronauts are not professional planners, however, and the complexity of schedules that novice planners can complete successfully is not fully understood. To identify the primary factors which contribute to scheduling task complexity, we conducted a human-in-the-loop study and developed planning algorithms to investigate how the type and amount of constraints affect the difficulty of scheduling and rescheduling. We created rankings of difficulty using a combination of human performance metrics from experimental planning tasks and metrics describing the final plans that participants scheduled. Using the results of our scheduling and rescheduling algorithm algorithms, we created a similar ranking with which to compare. We created rankings which compared well between the experimental and algorithm results for the scheduling task, but the rescheduling task proved more difficult to estimate.
Towards a Characterization of Scheduling Task Complexity
Future long-duration missions will require astronauts to act more autonomously, manage their schedules, and replan timelines as anomalies and discoveries occur. Astronauts are not professional planners, however, and the complexity of schedules that novice planners can complete successfully is not fully understood. To identify the primary factors which contribute to scheduling task complexity, we conducted a human-in-the-loop study and developed planning algorithms to investigate how the type and amount of constraints affect the difficulty of scheduling and rescheduling. We created rankings of difficulty using a combination of human performance metrics from experimental planning tasks and metrics describing the final plans that participants scheduled. Using the results of our scheduling and rescheduling algorithm algorithms, we created a similar ranking with which to compare. We created rankings which compared well between the experimental and algorithm results for the scheduling task, but the rescheduling task proved more difficult to estimate.
Automated platform management system scheduling
The Platform Management System (PMS) has been established to coordinate the operation of platform systems and payloads. Since platforms are to be out of contact with the ground more than the manned base, PMS functions are required to be more autonomous than those of the manned base. Automated replanning and rescheduling will be required to effectively and efficiently meet mission goals. In a FY88 study, we developed a phased approach to automated PMS scheduling based upon use of the same scheduling engine in both ground and space components. In the past year, we implemented a baseline, first phase, PMS scheduler prototype. Presently we are integrating this scheduler into two NASA Goddard Space Flight Center testbeds, as the ground scheduler in the Scheduling Concepts, Architectures, and Networks Testbed and as the onboard scheduler in the PMS Testbed. We will investigate rescheduling issues, evaluated operational performance and enhance the prototype to demonstrate our evolutionary approach to automated PMS scheduling.
Automated Platform Management System Scheduling
The Platform Management System was established to coordinate the operation of platform systems and instruments. The management functions are split between ground and space components. Since platforms are to be out of contact with the ground more than the manned base, the on-board functions are required to be more autonomous than those of the manned base. Under this concept, automated replanning and rescheduling, including on-board real-time schedule maintenance and schedule repair, are required to effectively and efficiently meet Space Station Freedom mission goals. In a FY88 study, we developed several promising alternatives for automated platform planning and scheduling. We recommended both a specific alternative and a phased approach to automated platform resource scheduling. Our recommended alternative was based upon use of exactly the same scheduling engine in both ground and space components of the platform management system. Our phased approach recommendation was based upon evolutionary development of the platform. In the past year, we developed platform scheduler requirements and implemented a rapid prototype of a baseline platform scheduler. Presently we are rehosting this platform scheduler rapid prototype and integrating the scheduler prototype into two Goddard Space Flight Center testbeds, as the ground scheduler in the Scheduling Concepts, Architectures, and Networks Testbed and as the on-board scheduler in the Platform Management System Testbed. Using these testbeds, we will investigate rescheduling issues, evaluate operational performance and enhance the platform scheduler prototype to demonstrate our evolutionary approach to automated platform scheduling. The work described in this paper was performed prior to Space Station Freedom rephasing, transfer of platform responsibility to Code E, and other recently discussed changes. We neither speculate on these changes nor attempt to predict the impact of the final decisions. As a consequence some of our work and results may be outdated when this paper is published.
Benefit Assessment of the Precision Departure Release Capability Concept
A Precision Departure Release Capability concept is being evaluated by both the National Aeronautics and Space Administration and the Federal Aviation Administration as part of a larger goal of improving throughput, efficiency and capacity in integrated departure, arrival and surface operations. The concept is believed to have the potential of increasing flight efficiency and throughput by avoiding missing assigned slots and minimizing speed increase or path stretch to recover the slot. The main thrust of the paper is determining the impact of early and late departures from the departure runway when an aircraft has a slot assigned either at a meter fix or at the arrival airport. Results reported in the paper are for two scenarios. The first scenario considers flights out of Dallas/Fort Worth destined for Hartsfield-Jackson International Airport in Atlanta flying through the Meridian meter-fix in the Memphis Center with miles-in-trail constraints. The second scenario considers flights destined to George Bush Intercontinental/Houston Airport with specified airport arrival rate constraint. Results show that delay reduction can be achieved by allowing reasonable speed changes in scheduling. It was determined that the traffic volume between Dallas/Fort Worth and Atlanta via the Meridian fix is low and the departures times are spread enough that large departure schedule uncertainty can be tolerated. Flights can depart early or late within 90 minutes without accruing much more delay due to miles-in-trail constraint at the Meridian fix. In the Houston scenario, 808 arrivals from 174 airports were considered. Results show that delay experienced by the 16 Dallas/Fort Worth departures is higher if initial schedules of the remaining 792 flights are kept unaltered while they are rescheduled. Analysis shows that the probability of getting the initially assigned slot back after perturbation and rescheduling decreases with increasing standard deviation of the departure delay distributions. Results show that most Houston arrivals can be expected to be on time based on the assumed zero-mean Normal departure delay distributions achievable by Precision Departure Release Capability. In the current system, airport-departure delay, which is the sum of gate-departure delay and taxi-out delay, is observed at the airports. This delay acts as a bias, which can be reduced by Precision Departure Release Capability.
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.
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.
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.
Exploring Self-Scheduling Strategies and Heuristics in Novice Schedulers
Missions beyond low Earth orbit will require crews to act with greater autonomy. Increasing communication delays will require crews to take on tasks currently supported by Mission Control, including the involved process of scheduling and rescheduling their own complex spaceflight timelines to fit a variety of restrictions and constraints. Astronauts, unlike Mission Control, are not expert planners, however, and determining simple strategies and heuristics that enable them to schedule successfully can increase the range of problems they can solve successfully. In two human-in-the-loop scheduling experiments, we analyzed 1) common strategies among novice schedules, and 2) the development of self-scheduling heuristics. We find that, even when participants are instructed to follow a given strategy, they rapidly develop their own self-scheduling heuristics as they learn to successfully complete the scheduling task. Participants conducting naturally learn to schedule activities with the most constraints first, while participants vary in heuristics in the rescheduling task.
Exploring Self-Scheduling Strategies and Heuristics in Novice Schedulers
Missions beyond low Earth orbit will require crews to act with greater autonomy. Increasing communication delays will require crews to take on tasks currently supported by Mission Control, including the involved process of scheduling and rescheduling their own complex spaceflight timelines to fit a variety of restrictions and constraints. Unlike Mission Control, astronauts are not expert planners, and determining strategies and heuristics that enable crews to schedule successfully may increase the range of problems they can solve. In two human-in-the-loop scheduling experiments, we analyzed 1) common strategies among novice schedulers and 2) the development of self-scheduling heuristics. We find that, even when participants are instructed to follow a given strategy, they rapidly develop their own self-scheduling heuristics as they learn to successfully complete the scheduling task. While scheduling, participants naturally learn to arrange activities with the most constraints first, whereas while rescheduling, they display greater variability in their heuristics.
The Role of Trust and Usability in Enabling Spaceflight Crew Autonomy
Future long duration exploration missions will require an increased use of onboard automated systems as spaceflight crews venture further than before and have longer communications delays with ground support. The design of these systems must support appropriate crew trust and have sufficient usability to enable spaceflight crew autonomy or risk being misused while crews wait to communicate with ground support. We evaluated trust & usability in our self-scheduling tool, Playbook, for crew mission timelines. Data was collected in a controlled lab experiment with 31 participants. Participants in the study conducted two tasks: scheduling, where participants were responsible for scheduling a majority of a day's operational tasks, and rescheduling, where participants were provided a schedule and asked to reschedule higher priority activities. We found a significant correlation between system trust and usability, irrespective of self-scheduling tasks. We conclude that system usability may play a bigger role in how trust is learned while conducting novel crew autonomy tasks such as self-scheduling. Future research should investigate the role of usability to encourage appropriate trust in onboard automated crew systems and enable crew autonomy.