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30 records · Page 2

Analysis of Eye-Tracking Data with Regards to the Complexity of Flight Deck Information Automation and Management - Inattentional Blindness, System State Awareness, and EFB Usage

In the constant drive to further the safety and efficiency of air travel, the complexity of avionics-related systems, and the procedures for interacting with these systems, appear to be on an ever-increasing trend. While this growing complexity often yields productive results with respect to system capabilities and flight efficiency, it can place a larger burden on pilots to manage increasing amounts of information and to understand intricate system designs. Evidence supporting this observation is becoming widespread, yet has been largely anecdotal or the result of subjective analysis. One way to gain more insight into this issue is through experimentation using more objective measures or indicators. This study utilizes and analyzes eye-tracking data obtained during a high-fidelity flight simulation study wherein many of the complexities of current flight decks, as well as those planned for the next generation air transportation system (NextGen), were emulated. The following paper presents the findings of this study with a focus on electronic flight bag (EFB) usage, system state awareness (SSA) and events involving suspected inattentional blindness (IB).

Dill, Evan T.↗

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.↗

FIM Avionics Operations Manual

This document describes the operation and use of the Flight Interval Management (FIM) Application installed on an electronic flight bag (EFB). Specifically, this document includes: 1) screen layouts for each page of the interface; 2) step-by-step instructions for data entry, data verification, and input error correction; 3) algorithm state messages and error condition alerting messages; 4) aircraft speed guidance and deviation indications; and 5) graphical display of the spatial relationships between the Ownship aircraft and the Target aircraft.

Alves, Erin E.↗

Deploying a Route Optimization EFB Application for Commercial Airline Operational Trials

The Traffic Aware Planner (TAP), developed for NASA Langley Research Center to support the Traffic Aware Strategic Aircrew Requests (TASAR) project, is a flight-efficiency software application developed for an Electronic Flight Bag (EFB). Tested in two flight trials and planned for operational testing by two commercial airlines, TAP is a real-time trajectory optimization application that leverages connectivity with onboard avionics and broadband Internet sources to compute and recommend route modifications to flight crews to improve fuel and time performance. The application utilizes a wide range of data, including Automatic Dependent Surveillance Broadcast (ADS-B) traffic, Flight Management System (FMS) guidance and intent, on-board sensors, published winds and weather, and Special Use Airspace (SUA) schedules. This paper discusses the challenges of developing and deploying TAP to various EFB platforms, our solutions to some of these challenges, and lessons learned, to assist commercial software developers and hardware manufacturers in their efforts to implement and extend TAP functionality in their environments. EFB applications (such as TAP) typically access avionics data via an ARINC 834 Simple Text Avionics Protocol (STAP) server hosted by an Aircraft Interface Device (AID) or other installed hardware. While the protocol is standardized, the data sources, content, and transmission rates can vary from aircraft to aircraft. Additionally, the method of communicating with the AID may vary depending on EFB hardware and/or the availability of onboard networking services, such as Ethernet, WIFI, Bluetooth, or other mechanisms. EFBs with portable and installed components can be implemented using a variety of operating systems, and cockpits are increasingly incorporating tablet-based technologies, further expanding the number of platforms the application may need to support. Supporting multiple EFB platforms, AIDs, avionics datasets, and user interfaces presents a challenge for software developers and the management of their code baselines. Maintaining multiple baselines to support all deployment targets can be extremely cumbersome and expensive. Certification also needs to be considered when developing the application. Regardless of whether the software is itself destined to be certified, data requirements in support of the application and user interface elements may introduce certification requirements for EFB manufacturers and the airlines. The example of TAP, the challenges faced, solutions implemented, and lessons learned will give EFB application and hardware developers insight into future potential requirements in deploying TAP or similar flight-deck EFB applications.

Roscoe, David A.↗

A Cockpit-Based Application for Traffic Aware Trajectory Optimization

The Traffic Aware Planner (TAP) is a cockpit-based advisory tool designed to be hosted on a Class 2 Electronic Flight Bag and developed to enable the concept of Traffic Aware Strategic Aircrew Requests (TASAR). This near-term concept provides pilots with optimized route changes that reduce fuel burn or flight time, avoids interactions with known traffic, weather and restricted airspace, and may be used by the pilots to request a trajectory change from air traffic control. TAP's internal architecture and algorithms are derived from the Autonomous Operations Planner, a flight-deck automation system developed by NASA to support research into aircraft self-separation. This paper reviews the architecture, functionality and operation of TAP.

TASAR↗

Human Automation Teaming: Lessons Learned and Future Directions

Full autonomy seems to be the goal for system developers in almost every area of the economy. However, as we move from automated systems to autonomous systems, designers have needed to insert humans to oversee automation that has traditionally been brittle or incomplete. This creates its own problems as the operator is usually out of the loop when the automation hands over problems that it cannot handle. To better handle these situations, it has been proposed that we develop human automation teams that have shared goals and objectives to support task performance. This paper will describe an initial model of Human Automation Teaming (HAT) which has three elements: transparency, bi-directional communications, and human-directed execution. Transparency in our model is a method for giving insight into the reasoning behind automated recommendations and actions, bi-directional communication allows the operator to communicate directly with the automation, and finally the automation defers execution to the human. The model was implemented through a number of features on an electronic flight bag (EFB) which are described in the paper. The EFB was installed in a mid-fidelity flight simulator and used by 12 airline pilots to support diversion decisions during off-nominal flight scenarios. Pilots reported that working with the HAT automation made diversion decisions easier and reduced their workload. They also reported that the information provided about diversion airports was similar to what they would receive from ground dispatch, thus making coordination with dispatch easier and less time consuming. These HAT features engender more trust in the automation when appropriate, and less when not, allowing improved supervision of automated functions by flight crews.

Human-Autonomy Teaming↗

Air Traffic Management Technology Demonstration-1 (ATD-1) Avionics Phase 2 Flight Test Training for Interval Management

Prior to the successful flight test validation of a new avionics prototype, participants from Boeing, Honeywell, and United Airlines underwent group training at NASA Langley Research Center. New prototype software for an algorithm which enables greater efficiency in high-density airspace, called Interval Management, was to be incorporated into Electronic Flight Bags and placed in the cockpit for pilot usage. The goals of the training were to teach the flight test pilots how to operate the new software, establish techniques to simultaneously position three aircraft prior to each test scenario, and ensure a common communication protocol among team members when coordinating the position of aircraft for the next scenario. The multi-tiered interactive training regimen consisted of a process that continually built upon previous foundational material. The primary learning elements were 1) a portable computer-based trainer that was provided to the pilots prior to classroom training sessions, 2) classroom learning, 3) full mock-up simulator training, and 4) refresher training just prior to the flight test. Each part of the regimen was designed to repeat and build upon the previous element. The purpose of this Technical Memorandum is to inform the aviation industry how flight training for Interval Management was conducted at Langley Research Center in order to reduce overall development costs of future Interval Management training programs. Secondly, the paper provides insight regarding the decision-making process when attempting to conduct a flight test.

Roper, Roy D.↗

DANTi, DAA in the Cockpit

DANTi is a prototype Electronic Flight Bag which incorporates an assistive Detect and Avoid (DAA) capability developed by NASA.

Maria Consiglio↗

Evaluation, Analysis and Results of the DANTi Flight Test Data, the DAIDALUS Detect and Avoid Algorithm, and the DANTi Concept for Detect and Avoid in the Cockpit

The DAIDALUS Detect and Avoid Algorithm [1] was developed to address the operational needs of Unmanned Aerial Systems (UAS) and meet the Minimum Operational Performance Standards for Detect and Avoid [2]. The DANTi (Detect and Avoid iN the cockpit) concept [3], developed at the National Aeronautics and Space Administration (NASA) Langley Research Center, leverages advancements achieved in surveillance and Detect and Avoid technologies for unmanned aircraft systems as a safety enhancing capability for pilots of manned aircraft. Pilots operating under Visual Flight Rules and not receiving Air Traffic Control radar services rely on see and avoid to remain well clear of other aircraft and avoid collisions. The DANTi concept has been conceived as a safety enhancement capability to remain well clear and avoid potential collisions. The DANTi concept uses a traffic display to provide situational awareness, conflict detection, alerting, and guidance to remain well clear.

Detect and Avoid↗

Assistive Detect and Avoid Technology in Urban Air Mobility Environments

The use of Assistive Detect and Avoid (Assistive DAA or ADAA) technology in Urban Air Mobility (UAM) environments poses potential benefits as well as challenges. Assistive DAA refers to the leveraged use of DAA technology, originally developed to replace see-and-avoid capabilities for remotely piloted aircraft, in onboard-piloted aircraft to augment (rather than replace) pilots’ see-and-avoid abilities and thus enhance the safety and efficiency of visual flight operations. ADAA is anticipated to be especially safety-enhancing in airspace where traffic density is high or traditional air traffic services are limited, such as in future UAM environments. ADAA may also enable higher-tempo UAM operations than with only see-and-avoid capabilities, while still maintaining acceptable levels of safety. UAM concepts under development by the FAA, NASA, and industry focus on operations moving people and cargo in urban and suburban areas using innovative technologies, operations, and aircraft, including electric vertical takeoff and landing (eVTOL) aircraft. Researchers at NASA Langley Research Center, in collaboration with FAA researchers at the William J. Hughes Technical Center in Atlantic City, NJ, have conducted a series of medium-fidelity, human-in-the-loop research simulations of potential future UAM operations and concepts in both Class C and Class B airspace environments. These simulations have included use of a Langley-developed ADAA research tool called DANTi, which enables configurable ADAA displays to be presented to pilots of simulated eVTOL aircraft participating in higher-density and higher-tempo UAM operations. Experience and observations made during testing of the NASA-developed DANTi ADAA capability in the UAM NFLITE simulation environment will be reported in this paper together with a discussion of airspace integration and regulatory topics.

Detect and Avoid↗

Assistive Detect and Avoid Technology in Urban Air Mobility Environments

The use of Assistive Detect and Avoid (Assistive DAA or ADAA) technology in Urban Air Mobility (UAM) environments poses potential benefits as well as challenges. Assistive DAA refers to the leveraged use of DAA technology, originally developed to replace see-and-avoid capabilities for remotely piloted aircraft, in onboard-piloted aircraft to augment (rather than replace) pilots’ see-and-avoid abilities and thus enhance the safety and efficiency of visual flight operations. ADAA is anticipated to be especially safety-enhancing in airspace where traffic density is high or traditional air traffic services are limited, such as in future UAM environments. ADAA may also enable higher-tempo UAM operations than with only see-and-avoid capabilities, while still maintaining acceptable levels of safety. UAM concepts under development by the FAA, NASA, and industry focus on operations moving people and cargo in urban and suburban areas using innovative technologies, operations, and aircraft, including electric vertical takeoff and landing (eVTOL) aircraft. Researchers at NASA Langley Research Center, in collaboration with FAA researchers at the William J. Hughes Technical Center in Atlantic City, NJ, have conducted a series of medium-fidelity, human-in-the-loop research simulations of potential future UAM operations and concepts in both Class C and Class B airspace environments. These simulations have included use of a Langley-developed ADAA research tool called DANTi, which enables configurable ADAA displays to be presented to pilots of simulated eVTOL aircraft participating in higher-density and higher-tempo UAM operations. Experience and observations made during testing of the NASA-developed DANTi ADAA capability in the UAM NFLITE simulation environment will be reported in this paper together with a discussion of airspace integration and regulatory topics.

Detect and Avoid↗

STS-91 Day 05 Highlights

On this fifth day of the STS-91 mission, the flight crew, Cmdr. Charles J. Precourt, Pilot Dominic L. Pudwill Gorie and Mission Specialists Wendy B. Lawrence, Franklin R. Chang-Diaz, Janet L. Kavandi, and Valery Victorovitch Ryumin and cosmonauts continue to move experiment hardware, logistical supplies and water between the two vehicles. They transfer additional bags of water from Discovery to Mir, bringing the total amount of water transferred to 683 pounds. Just over half of the 317 items scheduled to be transferred have now been moved between the two craft. Mission Specialists Wendy Lawrence and Janet Kavandi spend some time today checking out the shuttle's 50-foot long robot arm. This checkout evaluates new electronics and software for use on upcoming assembly missions for the new International Space Station. Today's checkout also tests the arm's dexterity in maneuvering around components of an orbiting space station.

Source record↗