Engineering topics

Battiste, Vernol

Publications and source records attributed to Battiste, Vernol.

At least 19 records

NASA NTRS2020

Urban Air Mobility System Testbed Using CAVE Virtual Reality Environment

Urban Air Mobility (UAM) refers to a system of air passenger and small cargo transportation within an urban area. The UAM framework also includes other urban Unmanned Aerial Systems (UAS) services that will be supported by a mix of onboard, ground, piloted, and autonomous operations. Over the past few years UAM research has gained wide interest from companies and federal agencies as an on-demand innovative transportation option that can help reduce traffic congestion and pollution as well as increase mobility in metropolitan areas. The concepts of UAM/UAS operation in the National Airspace System (NAS) remains an active area of research to ensure safe and efficient operations. With new developments in smart vehicle design and infrastructure for air traffic management, there is a need for methods to integrate and test various components of the UAM framework. In this work, we report on the development of a virtual reality (VR) testbed using the Cave Automatic Virtual Environment (CAVE) technology for human-automation teaming and airspace operation research of UAM. Using a four-wall projection system with motion capture, the CAVE provides an immersive virtual environment with real-time full body tracking capability. We created a virtual environment consisting of San Francisco city and a vertical take-off-and-landing passenger aircraft that can fly between a downtown location and the San Francisco International Airport. The aircraft can be operated autonomously or manually by a single pilot who maneuvers the aircraft using a flight control joystick. The interior of the aircraft includes a virtual cockpit display with vehicle heading, location, and speed information. The system can record simulation events and flight data for post-processing. The system parameters are customizable for different flight scenarios; hence, the CAVE VR testbed provides a flexible method for development and evaluation of UAM framework.

Marayong, Panadda↗

NASA NTRS2018

Urban Air Mobility Airspace Integration Concepts and Considerations

Urban Air Mobility (UAM) - defined as safe and efficient air traffic operations in a metropolitan area for manned aircraft and unmanned aircraft systems - is being researched and developed by industry, academia, and government. Significant resources have been invested toward cultivating an ecosystem for Urban Air Mobility that includes manufacturers of electric vertical takeoff and landing aircraft, builders of takeoff and landing areas, and researchers of the airspace integration concepts, technologies, and procedures needed to conduct Urban Air Mobility operations safely and efficiently alongside other airspace users. This paper provides high-level descriptions of both emergent and early expanded operational concepts for Urban Air Mobility that NASA is developing. The scope of this work is defined in terms of missions, aircraft, airspace, and hazards. Past and current Urban Air Mobility operations are also reviewed, and the considerations for the data exchange architecture and communication, navigation, and surveillance requirements are also discussed. This paper will serve as a starting point to develop a framework for NASA's Urban Air Mobility airspace integration research and development efforts with partners and stakeholders that could include fast-time simulations, human-in-the-loop (HITL) simulations, and flight demonstrations.

airspace integration↗

NASA NTRS2018

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↗

NASA NTRS2017

Measuring the Effectiveness of Human Autonomy Teaming

Human-Automation Teaming (HAT), is now recognized as a promising solution to the problems of humans managing increasingly complex work systems. A human-automation team can be defined as the interdependent coupling between one or more human operators and one or more autonomous systems requiring collaboration and coordination to accomplish system and task goals (e.g., Langan-Fox et al., 2009). In this conception, automated agents are considered team members that can operate at various levels of automation, be focused on one or more human-information-processing stages, and the interactions with human operators may be adaptable, adjustable or mixed initiative. We investigated some metrics for assessing HAT effectiveness in a demonstration of a HAT tool used by ground station operators in a Reduced Crew Operations project that was conducted at NASA Ames Human Automation Teaming Laboratory. In this paper, we focus on operator metrics of HAT effectiveness, specifically workload and operator behaviors.

measurements↗

NASA NTRS2017

Concept of Operations for RCO SPO

Reduced crew operations (RCO) refers to the reduction of crew members flying long-haul or military operations with more than one pilot onboard. Single pilot operations (SPO) refers to flying a commercial transport aircraft with only one pilot on board the aircraft, assisted by advanced onboard automation andor ground operators providing piloting support services. Properly implemented, RCO/SPO could provide operating cost savings while maintaining a level of safety no less than conventional two-pilot commercial operations. A concept of operations (ConOps) for any paradigm describes the characteristics of its various components and their integration in a multi-dimensional design space. This paper presents key options for humanautomation function allocation being considered by NASA in its ongoing development of RCO/SPO ConOps.

ConOps↗

NASA NTRS2016

System and Method for Providing a Real Time Audible Message to a Pilot

A system and method for providing information to a crew of the aircraft while in-flight. The system includes a module having: a receiver for receiving a message while in-flight; a filter having a set of screening parameters and operative to filter the message based on the set of screening parameters; and a converter for converting the message into an audible message. The message includes a pilot report having at least one of weather information, separation information, congestion information, flight deviation information and destination information. The message is sent to the aircraft by another aircraft or an air traffic controller.

Johnson, Walter W.↗

NASA NTRS2016

3D-CDTI User Manual v2.1

The 3D-Cockpit Display of Traffic Information (3D-CDTI) is a flight deck tool that presents aircrew with: proximal traffic aircraft location, their current status and flight plan data; strategic conflict detection and alerting; automated conflict resolution strategies; the facility to graphically plan manual route changes; time-based, in-trail spacing on approach. The CDTI is manipulated via a touchpad on the flight deck, and by mouse when presented as part of a desktop flight simulator.

3D CDTI↗

NASA NTRS2015

Effectiveness of Advanced Collaboration Tools on Crew Communication in Reduced Crew Operations

The present research examines operational performance and verbal communication in airline flight crews under reduced crew operations (RCO). Eighteen two-pilot crews flew six scenarios under three conditions; one condition involved current-day operations while two involved RCO. In RCO flights, the Captain initially operated the simulated aircraft alone but could request remote crewmember support as off-nominal events occurred and workload was expected to increase. In one of the two RCO conditions, crewmembers were provided with advanced prototype collaboration tools designed to alleviate difficulties in crew coordination. Crews successfully solved all challenging events without accident and analyses of operational performance did not reveal any differences among the three conditions. In RCO flights, crew communication increased when tools were available relative to flights in which they were not; specifically, there were more acknowledgements and decision-making communications. These results suggest the collaboration tools enable higher degrees of crewmember awareness andor coordination during distributed operations.

crew resource management↗

NASA NTRS2015

Pilot Situation Awareness and Its Implications for Single Pilot Operations: Analysis of a Human-In-The-Loop Study

In 2012, NASA began exploring the feasibility of single pilot/reduced crew operations in the context of scheduled air carrier operations. The current study examined how important it was for ground-based personnel providing support to single piloted aircraft (ground operators) to have opportunities to acquire situation awareness (SA) prior to being called on to assist an aircraft. We looked at two distinct concepts of operation, which varied in how much information was available to ground operators prior to being called on to assist a critical event (no vs. some Situation Preview). Thirty-five commercial pilots participated in the current study. Results suggested that a ground operators’ lack of initial SA when called on for dedicated assistance is not an issue, at least when the ground operator station displays environmental and systems data which are important to gaining overall SA of the specified aircraft. With appropriate displays, ground operators were able to provide immediate assistance, even if they had minimal SA prior to getting a request.

Reduced crew operations↗

NASA NTRS2015

Measured Response for UAS Integration into the National Airspace System

The measured response (MR) is the response time of aircraft to Air Traffic Controller (ATCo) commands and clearances. The overall MR can be broken up into several components, including the pilot verbal latencies (MR1), the time between the end of an ATCo clearance and the beginning of the pilots read back, and the execution initiation latency (MR2), the time between the end of the ATCos clearance and when the pilot begins to execute a maneuver. The MR is a crucial concern for the integration of Unmanned Aircraft Systems (UAS) into the National Airspace System (NAS) due to potentially greater latencies stemming from remote pilot communication and command execution. As a result, it is important to quantify what latencies in verbal responding and command execution are acceptable for safe and efficient operations in the NAS. The present studies begin to address these issues in a series of four simulations supported by the UAS Integration into the NAS program.

UAS in the NAS↗

NASA NTRS2014

Air Traffic Controller Performance and Acceptability of Multiple UAS in a Simulated NAS Environment

Previously, we showed that air traffic controllers (ATCos) rated UAS pilot verbal response latencies as acceptable when a 1.5 s delay was added to the UAS pilot responses, but a 5 s delay was rated as mostly unacceptable. In the present study we determined whether a 1.5 s added delay in the UAS pilots' verbal communications would affect ATCos interactions with UAS and other conventional aircraft when the number and speed of the UAS were manipulated. Eight radar-certified ATCos participated in this simulation. The ATCos managed a medium altitude sector containing arrival aircraft, en route aircraft, and one to four UAS. The UAS were conducting a surveillance mission and flew at either a "slow" or "fast" speed. We measured both UAS and conventional pilots' verbal communication latencies, and obtained ATCos' acceptability ratings for these latencies. Although the UAS pilot response latencies were longer than those of conventional pilots, the ATCos rated UAS pilot verbal communication latencies to be as acceptable as those of conventional pilots. Because the overall traffic load within the sector was held constant, ATCos only performed slightly worse when multiple UAS were in their sector compared to when only one UAS was in the sector. Implications of these findings for UAS integration in the NAS are discussed.

measured response↗

NASA NTRS2014

Toward Single Pilot Operations: The Impact of the Loss of Non-Verbal Communication on the Flight Deck

Since the 1950s, the crew required to fly transport category aircraft has been reduced from five to two. NASA is currently exploring the feasibility of a further reduction to one pilot. In this study we examine the effects of separating the pilots on crew interaction. The results are consistent with earlier research on decision-making between remote groups. Pilots strongly prefer face-to-face interactions; however, we could find no impact of separation on their ultimate decisions. There were a number of areas in which separation negatively affected communications. We discuss possible mitigations for these areas.

Single Pilot Operations↗

NASA NTRS2013

Influence of UAS Pilot Communication and Execution Delay on Controller's Acceptability Ratings of UAS-ATC Interactions

Successful integration of UAS in the NAS will require that UAS interactions with the air traffic management system be similar to interactions between manned aircraft and air traffic management. For example, UAS response times to air traffic controller (ATCo) clearances should be equivalent to those that are currently found to be acceptable with manned aircraft. Prior studies have examined communication delays with manned aircraft. Unfortunately, there is no analogous body of research for UAS. The goal of the present study was to determine how UAS pilot communication and execution delays affect ATCos' acceptability ratings of UAS pilot responses when the UAS is operating in the NAS. Eight radar-certified controllers managed traffic in a modified ZLA sector with one UAS flying in it. In separate scenarios, the UAS pilot verbal communication and execution delays were either short (1.5 s) or long (5 s) and either constant or variable. The ATCo acceptability of UAS pilot communication and execution delays were measured subjectively via post trial ratings. UAS verbal pilot communication delay, were rated as acceptable 92% of the time when the delay was short. This acceptability level decreased to 64% when the delay was long. UAS pilot execution delay had less of an influence on ATCo acceptability ratings in the present stimulation. Implications of these findings for UAS in the NAS integration are discussed.

communication↗

NASA NTRS2013

Effects of Type and Strength of Force Feedback on Movement Time in a Target Selection Task

Future cockpits will likely include new onboard technologies, such as cockpit displays of traffic information, to help support future flight deck roles and responsibilities. These new technologies may benefit from multimodal feedback to aid pilot information processing. The current study investigated the effects of multiple levels of force feedback on operator performance in an aviation task. Participants were presented with two different types of force feedback (gravitational and spring force feedback) for a discrete targeting task, with multiple levels of gain examined for each force feedback type. Approach time and time in target were recorded. Results suggested that the two highest levels of gravitational force significantly reduced approach times relative to the lowest level of gravitational force. Spring force level only affected time in target. Implications of these findings for the design of future cockpit displays will be discussed.

CDTI↗

NASA NTRS2013

NASA's Single-Pilot Operations Technical Interchange Meeting: Proceedings and Findings

Researchers at the National Aeronautics and Space Administration (NASA) Ames Research Center and Langley Research Center are jointly investigating issues associated with potential concepts, or configurations, in which a single pilot might operate under conditions that are currently reserved for a minimum of two pilots. As part of early efforts, NASA Ames Research Center hosted a technical interchange meeting in order to gain insight from members of the aviation community regarding single-pilot operations (SPO). The meeting was held on April 10-12, 2012 at NASA Ames Research Center. Professionals in the aviation domain were invited because their areas of expertise were deemed to be directly related to an exploration of SPO. NASA, in selecting prospective participants, attempted to represent various relevant sectors within the aviation domain. Approximately 70 people representing government, academia, and industry attended. A primary focus of this gathering was to consider how tasks and responsibilities might be re-allocated to allow for SPO.

post NextGen↗

NASA NTRS2012

Intuitiveness of Symbol Features for Air Traffic Management

We present the results of two online surveys asking participants to indicate what type of air traffic information might be conveyed by a number of symbols and symbol features (color, fill, text, and shape). The results of this initial study suggest that the well-developed concepts of ownership, altitude, and trajectory are readily associated with certain symbol features, while the relatively novel concept of equipage was not clearly associated with any specific symbol feature.

Ngo, Mary Kim↗

NASA NTRS2012

An Evaluation of Controller and Pilot Performance, Workload and Acceptability under a NextGen Concept for Dynamic Weather Adapted Arrival Routing

In todays terminal operations, controller workload increases and throughput decreases when fixed standard terminal arrival routes (STARs) are impacted by storms. To circumvent this operational constraint, Prete, Krozel, Mitchell, Kim and Zou (2008) proposed to use automation to dynamically adapt arrival and departure routing based on weather predictions. The present study examined this proposal in the context of a NextGen trajectory-based operation concept, focusing on the acceptability and its effect on the controllers ability to manage traffic flows. Six controllers and twelve transport pilots participated in a human-in-the-loop simulation of arrival operations into Louisville International Airport with interval management requirements. Three types of routing structures were used: Static STARs (similar to current routing, which require the trajectories of individual aircraft to be modified to avoid the weather), Dynamic routing (automated adaptive routing around weather), and Dynamic Adjusted routing (automated adaptive routing around weather with aircraft entry time adjusted to account for differences in route length). Spacing Responsibility, whether responsibility for interval management resided with the controllers (as today), or resided with the pilot (who used a flight deck based automated spacing algorithm), was also manipulated. Dynamic routing as a whole was rated superior to static routing, especially by pilots, both in terms of workload reduction and flight path safety. A downside of using dynamic routing was that the paths flown in the dynamic conditions tended to be somewhat longer than the paths flown in the static condition.

Johnson, Walter W.↗

NASA NTRS2012

Comparison of Controller and Flight Deck Algorithm Performance During Interval Management with Dynamic Arrival Trees (STARS)

Managing the interval between arrival aircraft is a major part of the en route and TRACON controller s job. In an effort to reduce controller workload and low altitude vectoring, algorithms have been developed to allow pilots to take responsibility for, achieve and maintain proper spacing. Additionally, algorithms have been developed to create dynamic weather-free arrival routes in the presence of convective weather. In a recent study we examined an algorithm to handle dynamic re-routing in the presence of convective weather and two distinct spacing algorithms. The spacing algorithms originated from different core algorithms; both were enhanced with trajectory intent data for the study. These two algorithms were used simultaneously in a human-in-the-loop (HITL) simulation where pilots performed weather-impacted arrival operations into Louisville International Airport while also performing interval management (IM) on some trials. The controllers retained responsibility for separation and for managing the en route airspace and some trials managing IM. The goal was a stress test of dynamic arrival algorithms with ground and airborne spacing concepts. The flight deck spacing algorithms or controller managed spacing not only had to be robust to the dynamic nature of aircraft re-routing around weather but also had to be compatible with two alternative algorithms for achieving the spacing goal. Flight deck interval management spacing in this simulation provided a clear reduction in controller workload relative to when controllers were responsible for spacing the aircraft. At the same time, spacing was much less variable with the flight deck automated spacing. Even though the approaches taken by the two spacing algorithms to achieve the interval management goals were slightly different they seem to be simpatico in achieving the interval management goal of 130 sec by the TRACON boundary.

Battiste, Vernol↗