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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.

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NASA NTRS2016

Performance Evaluation of SARDA: An Individual Aircraft-Based Advisory Concept for Surface Management

Surface operations at airports in the US are based on tactical operations, where departure aircraft primarily queue up and wait at the departure runways. NASAs Spot And Runway Departure Advisor (SARDA) tool was developed to address these inefficiencies through Air Traffic Control Tower advisories. The SARDA system is being updated to include collaborative gate hold, either tactically or strategically. This paper presents the results of the human-in-the-loop evaluation of the tactical gate hold version of SARDA in a 360 degree simulated tower setting. The simulations were conducted for the east side of the Dallas-Fort Worth airport. The new system provides gate hold, ground controller and local controller advisories based on a single scheduler. Simulations were conducted with SARDA on and off, the off case reflecting current day operations with no gate hold. Scenarios based on medium (1.2x current levels) and heavy (1.5x current levels) traffic were explored. Data collected from the simulation was analyzed for runway usage, delay for departures and arrivals, and fuel consumption. Further, Traffic Management Initiatives were introduced for a subset of the aircraft. Results indicated that runway usage did not change with the use of SARDA, i.e., there was no loss in runway throughput as compared to baseline. Taxiing delay was significantly reduced with the use of advisory by 45 in medium scenarios and 60 in heavy. Arrival delay was unaffected by the use of advisory. Total fuel consumption was also reduced by 23 in medium traffic and 33 in heavy. TMI compliance appeared unaffected by the advisory.

Yoon Jung↗
NASA NTRS2015

The Effectiveness of a Route Crossing Tool in a Simulated New York Airspace

Congested airspace is the cause of many delays in the terminal area and these delays can have a ripple effect on the rest of a nation's airspace. The New York terminal area is an example of where this happens in the U. S. An important goal, therefore, is to increase the efficiency of operations in congested terminal airspace where possible. Modeling studies of arrival and departure flows have shown that sharing of arrival and departure airspace increases efficiency in terminal operations. One source of inefficiency in terminal operations is that departure aircraft are frequently held level under arrival flows when it would be more efficient to climb the departure aircraft earlier. A Route Crossing Tool was developed to help controllers climb Newark (EWR) departures to the south earlier by temporarily sharing airspace with arrivals coming into LaGuardia (LGA) from the south. Instead of flying under the arrivals, a departure to the south could climb earlier by flying through the arrival airspace if there was a suitable gap between arrivals. A Human-in-the-Loop (HITL) simulation was conducted in this environment which compared three tool conditions: Baseline (no tool), a Single Route Crossing tool in which one route through the arrival flow was evaluated for crossing, and a Multi-Route Crossing tool in which five parallel routes were evaluated. In all conditions, the departures could be held level under the arrival flow. The results showed that controllers climbed a higher proportion of departures in the Multi-Route tool condition than in the other two conditions, with a higher proportion of departures climbed in smaller gaps and in front of trailing arrivals. The controllers indicated that the Multi-Route and Single Route tools helped them estimate distances more accurately and rated safety, workload, and coordination in the simulation as acceptable.

terminal airspace↗
NASA NTRS2015

The Impact of Integrated Maneuver Guidance Information on UAS Pilots Performing the Detect and Avoid Task

The integrated human-in-the-loop (iHITL) simulation examined the effect of four different Detect-and-Avoid (DAA) display concepts on unmanned aircraft system (UAS) pilots' ability to maintain safe separation. The displays varied in the type and amount of guidance they provided to pilots. The study's background and methodology are discussed, followed by the 'measured response' data (i.e., pilots' end-to-end response time in reacting to traffic alerts on their DAA display). Results indicate that display type had a significant impact on how long pilot's spent interacting with the interface (i.e., edit times).

detect and avoid↗
NASA NTRS2016

The Impact of Suggestive Maneuver Guidance on UAS Pilots Performing the Detect and Avoid Function

This presentation discusses the results of a recent UAS Integration into the NAS human-in-the-loop simulation. In the study, 16 active UAS pilots flew a UAS through civil airspace and were tasked with maintaining well clear from other aircraft in the area. Pilots performed the task with four different detect and avoid (DAA) traffic displays, each of which varied in the form of guidance it provided to pilots The present findings focus on how the different displays impacted pilots' measured response to scripted conflicts with their aircraft. Measured response is made up of several components, each of which help inform our understanding of the pilots' role in the overall detect and avoid task.

detect and avoid↗
NASA NTRS2014

UAS Integration into the NAS: iHTL: DAA Display Evaluation Preliminary Results

The integrated human-in-the-loop (iHITL) simulation examined the effect of four different Detect-and-Avoid (DAA) display concepts on unmanned aircraft system (UAS) pilots' ability to maintain safe separation. The displays varied in the type and amount of guidance they provided to pilots. The study's background and methodology are discussed, followed by a presentation of the preliminary 'measured response' data (i.e., pilots' end-to-end response time in reacting to traffic alerts on their DAA display). Results indicate that display type had moderate to no affect on pilot measured response times.

unmanned aircraft systems↗
NASA NTRS2016

Taxi Time Prediction at Charlotte Airport Using Fast-Time Simulation and Machine Learning Techniques

Accurate taxi time prediction is required for enabling efficient runway scheduling that can increase runway throughput and reduce taxi times and fuel consumptions on the airport surface. Currently NASA and American Airlines are jointly developing a decision-support tool called Spot and Runway Departure Advisor (SARDA) that assists airport ramp controllers to make gate pushback decisions and improve the overall efficiency of airport surface traffic. In this presentation, we propose to use Linear Optimized Sequencing (LINOS), a discrete-event fast-time simulation tool, to predict taxi times and provide the estimates to the runway scheduler in real-time airport operations. To assess its prediction accuracy, we also introduce a data-driven analytical method using machine learning techniques. These two taxi time prediction methods are evaluated with actual taxi time data obtained from the SARDA human-in-the-loop (HITL) simulation for Charlotte Douglas International Airport (CLT) using various performance measurement metrics. Based on the taxi time prediction results, we also discuss how the prediction accuracy can be affected by the operational complexity at this airport and how we can improve the fast time simulation model before implementing it with an airport scheduling algorithm in a real-time environment.

airport surface traffic↗
NASA NTRS2015

UAS Integration into the NAS: Detect and Avoid Display Evaluations in Support of SC-228 MOPS Development

This presentation provides an overview of the work the Human Systems Integration (HSI) sub-project has done on detect and avoid (DAA) displays while working on the UAS Integration into the NAS project. Much of the work has been used to support the ongoing development of minimum operational performance standards (MOPS) for UAS by RTCA Special Committee 228. The design and results of three different human-in-the-loop simulations are discussed, with particular emphasis on the role of the UAS pilot in the Self Separation Timeline.

unmanned aircraft systems↗
NASA NTRS2015

Statistical Engineering in Air Traffic Management Research

NASA is working to develop an integrated set of advanced technologies to enable efficient arrival operations in high-density terminal airspace for the Next Generation Air Transportation System. This integrated arrival solution is being validated and verified in laboratories and transitioned to a field prototype for an operational demonstration at a major U.S. airport. Within NASA, this is a collaborative effort between Ames and Langley Research Centers involving a multi-year iterative experimentation process. Designing and analyzing a series of sequential batch computer simulations and human-in-the-loop experiments across multiple facilities and simulation environments involves a number of statistical challenges. Experiments conducted in separate laboratories typically have different limitations and constraints, and can take different approaches with respect to the fundamental principles of statistical design of experiments. This often makes it difficult to compare results from multiple experiments and incorporate findings into the next experiment in the series. A statistical engineering approach is being employed within this project to support risk-informed decision making and maximize the knowledge gained within the available resources. This presentation describes a statistical engineering case study from NASA, highlights statistical challenges, and discusses areas where existing statistical methodology is adapted and extended.

Wilson, Sara R.↗
NASA NTRS2016

NY TBO Research: Integrated Demand Management (IDM): IDM Concept, Tools, and Training Package

A series of human-in-the-loop simulation sessions were conducted in the Airspace Operations Laboratory (AOL) to evaluate a new traffic management concept called Integrated Demand Management (IDM). The simulation explored how to address chronic equity, throughput and delay issues associated with New Yorks high-volume airports by operationally integrating three current and NextGen capabilities the Collaborative Trajectory Options Program (CTOP), Time-Based Flow Management (TBFM) and Required Time of Arrival (RTA) in order to better manage traffic demand within the National Air Traffic System. A package of presentation slides was developed to describe the concept, tools, and training materials used in the simulation sessions. The package will be used to outbrief our stakeholders by both presenting orally and disseminating of the materials via email.

trajectory-based operations↗
NASA NTRS2016

Operational Characteristics Identification and Simulation Model Verification for Incheon International Airport

Incheon International Airport (ICN) is one of the hub airports in East Asia. Airport operations at ICN have been growing more than 5% per year in the past five years. According to the current airport expansion plan, a new passenger terminal will be added and the current cargo ramp will be expanded in 2018. This expansion project will bring 77 new stands without adding a new runway to the airport. Due to such continuous growth in airport operations and future expansion of the ramps, it will be highly likely that airport surface traffic will experience more congestion, and therefore, suffer from efficiency degradation. There is a growing awareness in aviation research community of need for strategic and tactical surface scheduling capabilities for efficient airport surface operations. Specific to ICN airport operations, a need for A-CDM (Airport - Collaborative Decision Making) or S-CDM(Surface - Collaborative Decision Making), and controller decision support tools for efficient air traffic management has arisen since several years ago. In the United States, there has been independent research efforts made by academia, industry, and government research organizations to enhance efficiency and predictability of surface operations at busy airports. Among these research activities, the Spot and Runway Departure Advisor (SARDA) developed and tested by National Aeronautics and Space Administration (NASA) is a decision support tool to provide tactical advisories to the controllers for efficient surface operations. The effectiveness of SARDA concept, was successfully verified through the human-in-the-loop (HITL) simulations for both spot release and runway operations advisories for ATC Tower controllers of Dallas/Fort Worth International Airport (DFW) in 2010 and 2012, and gate pushback advisories for the ramp controller of Charlotte/Douglas International Airport (CLT) in 2014. The SARDA concept for tactical surface scheduling is further enhanced and is being integrated into NASA's Airspace Technology Demonstration - 2 (ATD-2) project for technology demonstration of Integrated Arrival/Departure/Surface (ADS) operations at CLT. This study is a part of the international research collaboration between KAIA (Korea Agency for Infrastructure Technology Advancement)/KARI (Korea Aerospace Research Institute) and NASA, which is being conducted to validate the effectiveness of SARDA concept as a controller decision support tool for departure and surface management of ICN. This paper presents the preliminary results of the collaboration effort. It includes investigation of the operational environment of ICN, data analysis for identification of the operational characteristics of the airport, construction and verification of airport simulation model using Surface Operations Simulator and Scheduler (SOSS), NASA's fast-time simulation tool.

scheduling↗
NASA NTRS2016

Operational Characteristics Identification and Simulation Model Verification for Incheon International Airport

Incheon International Airport (ICN) is one of the hub airports in East Asia. Airport operations at ICN have been growing more than 5 percent per year in the past five years. According to the current airport expansion plan, a new passenger terminal will be added and the current cargo ramp will be expanded in 2018. This expansion project will bring 77 new stands without adding a new runway to the airport. Due to such continuous growth in airport operations and future expansion of the ramps, it will be highly likely that airport surface traffic will experience more congestion, and therefore, suffer from efficiency degradation. There is a growing awareness in aviation research community of need for strategic and tactical surface scheduling capabilities for efficient airport surface operations. Specific to ICN airport operations, a need for A-CDM (Airport - Collaborative Decision Making) or S-CDM (Surface - Collaborative Decision Making), and controller decision support tools for efficient air traffic management has arisen since several years ago. In the United States, there has been independent research efforts made by academia, industry, and government research organizations to enhance efficiency and predictability of surface operations at busy airports. Among these research activities, the Spot and Runway Departure Advisor (SARDA) developed and tested by National Aeronautics and Space Administration (NASA) is a decision support tool to provide tactical advisories to the controllers for efficient surface operations. The effectiveness of SARDA concept, was successfully verified through the human-in-the-loop (HITL) simulations for both spot release and runway operations advisories for ATC Tower controllers of Dallas-Fort Worth International Airport (DFW) in 2010 and 2012, and gate pushback advisories for the ramp controller of Charlotte-Douglas International Airport (CLT) in 2014. The SARDA concept for tactical surface scheduling is further enhanced and is being integrated into NASA's Airspace Technology Demonstration-2 (ATD-2) project for technology demonstration of Integrated Arrival-Departure-Surface (IADS) operations at CLT. This study is a part of the international research collaboration between KAIA (Korea Agency for Infrastructure Technology Advancement), KARI (Korea Aerospace Research Institute) and NASA, which is being conducted to validate the effectiveness of SARDA concept as a controller decision support tool for departure and surface management of ICN. This paper presents the preliminary results of the collaboration effort. It includes investigation of the operational environment of ICN, data analysis for identification of the operational characteristics of the airport, construction and verification of airport simulation model using Surface Operations Simulator and Scheduler (SOSS), NASA's fast-time simulation tool.

surface operations analysis↗
NASA NTRS2015

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↗
NASA NTRS2016

Traffic Aware Planner for Cockpit-Based Trajectory Optimization

The Traffic Aware Planner (TAP) software application is a cockpit-based advisory tool designed to be hosted on an Electronic Flight Bag and to enable and test the NASA concept of Traffic Aware Strategic Aircrew Requests (TASAR). The TASAR concept provides pilots with optimized route changes (including altitude) that reduce fuel burn and/or flight time, avoid interactions with known traffic, weather and restricted airspace, and may be used by the pilots to request a route and/or altitude change from Air Traffic Control. Developed using an iterative process, TAP's latest improvements include human-machine interface design upgrades and added functionality based on the results of human-in-the-loop simulation experiments and flight trials. Architectural improvements have been implemented to prepare the system for operational-use trials with partner commercial airlines. Future iterations will enhance coordination with airline dispatch and add functionality to improve the acceptability of TAP-generated route-change requests to pilots, dispatchers, and air traffic controllers.

Woods, Sharon E.↗
NASA NTRS2016

Flight Crew Responses to the Interval Management Alternative Clearances (IMAC) Experiment

Interval Management Alternative Clearances (IMAC) was a human-in-the-loop simulation experiment conducted to explore the efficacy and acceptability of three IM operations: CAPTURE, CROSS, and MAINTAIN. Two weeks of data collection were conducted, with each week using twelve subject pilots and four subject controllers flying ten high-density arrival scenarios into the Denver International Airport. Overall, both the IM operations and procedures were rated very favorably by the flight crew in terms of acceptability, workload, and pilot head down time. However, several critical issues were identified requiring resolution prior to real-world implementation, including the high frequency of IM speed commands, IM speed commands requiring changes to aircraft configuration, and ambiguous IM cockpit displays that did not trigger the intended pilot reaction. The results from this experiment will be used to prepare for a flight test in 2017, and to support the development of an advanced IM concept of operations by the FAA (Federal Aviation Agency) and aviation industry.

Baxley, Brian T.↗
NASA NTRS2016

System Performance of an Integrated Airborne Spacing Algorithm with Ground Automation

The National Aeronautics and Space Administration's (NASA's) first Air Traffic Management (ATM) Technology Demonstration (ATD-1) was created to facilitate the transition of mature ATM technologies from the laboratory to operational use. The technologies selected for demonstration are the Traffic Management Advisor with Terminal Metering (TMA-TM), which provides precise time-based scheduling in the Terminal airspace; Controller Managed Spacing (CMS), which provides controllers with decision support tools to enable precise schedule conformance; and Interval Management (IM), which consists of flight deck automation that enables aircraft to achieve or maintain precise spacing behind another aircraft. Recent simulations and IM algorithm development at NASA have focused on trajectory-based IM operations where aircraft equipped with IM avionics are expected to achieve a spacing goal, assigned by air traffic controllers, at the final approach fix. The recently published IM Minimum Operational Performance Standards describe five types of IM operations. This paper discusses the results and conclusions of a human-in-the-loop simulation that investigated three of those IM operations. The results presented in this paper focus on system performance and integration metrics. Overall, the IM operations conducted in this simulation integrated well with ground-based decisions support tools and certain types of IM operational were able to provide improved spacing precision at the final approach fix; however, some issues were identified that should be addressed prior to implementing IM procedures into real-world operations.

Swieringa, Kurt A.↗
NASA NTRS2016

Cardiac-Activity Measures for Assessing Airport Ramp-Tower Controller's Workload

Heart rate (HR) and heart rate variability (HRV) potentially offer objective, continuous, and non-intrusive measures of human-operator's mental workload. Such measurement capability is attractive for workload assessment in complex laboratory simulations or safety-critical field testing. The present study compares mean HR and HRV data with self-reported subjective workload ratings collected during a high-fidelity human-in-the-loop simulation of airport ramp traffic control operations, which involve complex cognitive and coordination tasks. Mean HR was found to be weakly sensitive to the workload ratings, while HRV was not sensitive or even contradictory to the assumptions. Until more knowledge on stress response mechanisms of the autonomic nervous system is obtained, it is recommended that these cardiac-activity measures be used with other workload assessment tools, such as subjective measures.

Hayashi, Miwa↗
NASA NTRS2016

Cardiac-Activity Measures for Assessing Airport Ramp-Tower Controller's Workload

Heart rate (HR) and heart rate variability (HRV) potentially offer objective, continuous, and non-intrusive measures of human-operators mental workload. Such measurement capability is attractive for workload assessment in complex laboratory simulations or safety-critical field testing. The present study compares mean HR and HRV data with self-reported subjective workload ratings collected during a high-fidelity human-in-the-loop simulation of airport ramp traffic control operations, which involve complex cognitive and coordination tasks. Mean HR was found to be weakly sensitive to the workload ratings, while HRV was not sensitive or even contradictory to the assumptions. Until more knowledge on stress response mechanisms of the autonomic nervous system is obtained, it is recommended that these cardiac-activity measures be used with other workload assessment tools, such as subjective measures.

Hayashi, Miwa↗
NASA NTRS2016

Effects of Transparency on Pilot Trust and Agreement in the Autonomous Constrained Flight Planner

We performed a human-in-the-loop study to explore the role of transparency in engendering trust and reliance within highly automated systems. Specifically, we examined how transparency impacts trust in and reliance upon the Autonomous Constrained Flight Planner (ACFP), a critical automated system being developed as part of NASA's Reduced Crew Operations (RCO) Concept. The ACFP is designed to provide an enhanced ground operator, termed a super dispatcher, with recommended diversions for aircraft when their primary destinations are unavailable. In the current study, 12 commercial transport rated pilots who played the role of super dispatchers were given six time-pressured all land scenarios where they needed to use the ACFP to determine diversions for multiple aircraft. Two factors were manipulated. The primary factor was level of transparency. In low transparency scenarios the pilots were given a recommended airport and runway, plus basic information about the weather conditions, the aircraft types, and the airport and runway characteristics at that and other airports. In moderate transparency scenarios the pilots were also given a risk evaluation for the recommended airport, and for the other airports if they requested it. In the high transparency scenario additional information including the reasoning for the risk evaluations was made available to the pilots. The secondary factor was level of risk, either high or low. For high-risk aircraft, all potential diversions were rated as highly risky, with the ACFP giving the best option for a bad situation. For low-risk aircraft the ACFP found only low-risk options for the pilot. Both subjective and objective measures were collected, including rated trust, whether the pilots checked the validity of the automation recommendation, and whether the pilots eventually flew to the recommended diversion airport. Key results show that: 1) Pilots trust increased with higher levels of transparency, 2) Pilots were more likely to verify ACFPs recommendations with low levels of transparency and when risk was high, 3) Pilots were more likely to explore other options from the ACFP in low transparency conditions and when risk was high, and 4) Pilots decision to accept or reject ACFPs recommendations increased as a function of the transparency in the explanation. The finding that higher levels of transparency was coupled with higher levels of trust, a lower need to verify other options, and higher levels of agreement with ACFP recommendations, confirms the importance of transparency in aiding reliance on automated recommendations. Additional analyses of qualitative data gathered from subjects through surveys and during debriefing interviews also provided the basis for new design recommendations for the ACFP.

trust↗