Anna C. Trujillo

Floor/shoe slip resistance measurement

A variety of slip measurement devices exist that provide estimates of both static and dynamic coefficient-of-friction (COF) values between ones shoes and the floor. Unfortunately, different shoe sole/heel materials, floor conditions, and contaminants will affect the tests in ways that result in widely varying COF estimates. This paper reviews the basic physics of such tests and describes a set of experiments to determine the static and dynamic COF values under operating conditions known to exist in different jobs. The results define a set of conditions wherein low (hazardous) COF values would exist (e.g., hard Neolite shoe material in contact with a wet, smooth walking surface). The results also question the use of light-load testing devices and static and slow speed reference COF values in the literature.

A trajectory-generation framework for time-critical cooperative missions

This paper introduces a heuristic planar trajectory-generation framework for multiple vehicles. Desired feasible trajectories are generated using Pythagorean Hodograph Bézier curves that satisfy the dynamic constraints of the vehicles, and guarantee spatial separation between the paths for safe operation. It is shown that the trajectory generation framework can be cast into a constrained optimization problem where a set of (sub)optimal desired trajectories are obtained by minimizing a cost function. To show the efficiency of the algorithm, a simulation example is given, where three fixed-wing Unmanned Aerial Vehicles are following and coordinating along feasible trajectories that are generated by the algorithm.

A Natural Interaction Interface for UAVs Using Intuitive Gesture Recognition

The popularity of unmanned aerial vehicles (UAVs) is increasing as technological advancements boost their favorability for a broad range of applications. One application is science data collection. In fields like earth and atmospheric science, researchers are seeking to use UAVs to augment their current portfolio of platforms and increase their accessibility to geographic areas of interest. By increasing the number of data collection platforms, UAVs will significantly improve system robustness and allow for more sophisticated studies. Scientists would like the ability to deploy an available fleet of UAVs to traverse a desired flight path and collect sensor data without needing to understand the complex low-level controls required to describe and coordinate such a mission. A natural interaction interface for a Ground Control System (GCS) using gesture recognition is developed to allow non-expert users (e.g., scientists) to define a complex flight path for a UAV using intuitive hand gesture inputs from the constructed gesture library. The GCS calculates the combined trajectory on-line, verifies the trajectory with the user, and sends it to the UAV controller to be flown.

Pilot performance with predictive system status information

Research has shown a strong pilot preference for predictive information of aircraft system status in the flight deck. However, the benefits of predictive information have not been quantitatively demonstrated. The study described here attempted to identify and quantify these benefits if they existed. In this simulator experiment, three types of predictive information (none, whether a parameter was changing abnormally, and the time for a parameter to reach an alert range) and four initial times to an alert (1 minute, 5 minutes, 15 minutes, and ETA+45 minutes) were found to affect when subjects accomplished certain actions, such as accessing pertinent checklists, declaring emergencies, diverting, and calling the flight attendant and dispatch.

Pilot preferences on displayed aircraft control variables

The experiments described here explored how pilots want available maneuver authority information transmitted and how this information affects pilots before and after an aircraft failure. The aircraft dynamic variables relative to flight performance were narrowed to energy management variables. A survey was conducted to determine what these variables should be. Survey results indicated that bank angle, vertical velocity, and airspeed were the preferred variables. Based on this, two displays were designed to inform the pilot of available maneuver envelope expressed as bank angle, vertical velocity, and airspeed. These displays were used in an experiment involving control surface failures. Results indicate the displayed limitations in bank angle, vertical velocity, and airspeed were helpful to the pilots during aircraft surface failures. However, the additional information did lead to a slight increase in workload, a small decrease in perceived aircraft flying qualities, and no effect on aircraft situation awareness.

Paper to Electronic Questionnaires: Effects on Structured Questionnaire Forms

With the use of computers, paper questionnaires are being replaced by electronic questionnaires. The formats of traditional paper questionnaires have been found to affect a subjects rating. Consequently, the transition from paper to electronic format can subtly change results. The research presented begins to determine how electronic questionnaire formats change subjective ratings. For formats where subjects used a flow chart to arrive at their rating, starting at the worst and middle ratings of the flow charts were the most accurate but subjects took slightly more time to arrive at their answers. Except for the electronic paper format, starting at the worst rating was the most preferred. The paper and electronic paper versions had the worst accuracy. Therefore, for flowchart type of questionnaires, flowcharts should start at the worst rating and work their way up to better ratings.

Flight Envelope Information-Augmented Display for Enhanced Pilot Situation Awareness

This paper presents an interface system display which is conceived to improve pilot situation awareness with respect to a flight envelope protection system developed for a mid-sized transport aircraft. The new display is designed to complement existing cockpit displays, and to augment them with information that relates to both aircraft state and the control automation itself. In particular, the proposed display provides cues about the state of automation directly in terms of pilot control actions, in addition to flight parameters. The paper also describes a forthcoming evaluation test plan that is intended to validate the developed interface by assessing the relevance of the displayed information, as well as the adequacy of the display layout.

Collaborating with Autonomous Agents

With the anticipated increase of small unmanned aircraft systems (sUAS) entering into the National Airspace System, it is highly likely that vehicle operators will be teaming with fleets of small autonomous vehicles. The small vehicles may consist of sUAS, which are 55 pounds or less that typically will y at altitudes 400 feet and below, and small ground vehicles typically operating in buildings or defined small campuses. Typically, the vehicle operators are not concerned with manual control of the vehicle; instead they are concerned with the overall mission. In order for this vision of high-level mission operators working with fleets of vehicles to come to fruition, many human factors related challenges must be investigated and solved. First, the interface between the human operator and the autonomous agent must be at a level that the operator needs and the agents can understand. This paper details the natural language human factors e orts that NASA Langleys Autonomy Incubator is focusing on. In particular these e orts focus on allowing the operator to interact with the system using speech and gestures rather than a mouse and keyboard. With this ability of the system to understand both speech and gestures, operators not familiar with the vehicle dynamics will be able to easily plan, initiate, and change missions using a language familiar to them rather than having to learn and converse in the vehicles language. This will foster better teaming between the operator and the autonomous agent which will help lower workload, increase situation awareness, and improve performance of the system as a whole.

Operating in "Strange New Worlds" and Measuring Success - Test and Evaluation in Complex Environments

Software tools are being developed by the Autonomy Incubator at NASAs Langley Research Center that will provide an integrated and scalable capability to support research and non-research flight operations across several flight domains, including urban and mixed indoor-outdoor operations. These tools incorporate a full range of data products to support mission planning, approval, flight operations, and post-flight review. The system can support a number of different operational scenarios that can incorporate live and archived data streams for UAS operators, airspace regulators, and other important stakeholders. Example use cases are described that illustrate how the tools will benefit a variety of users in nominal and off-nominal operational scenarios. An overview is presented for the current state of the toolset, including a summary of current demonstrations that have been completed. Details of the final, fully operational capability are also presented, including the interfaces that will be supported to ensure compliance with existing and future airspace operations environments.

Preliminary Exploration of Adaptive State Predictor Based Human Operator Modeling

Control-theoretic modeling of the human operator dynamic behavior in manual control tasks has a long and rich history. In the last two decades, there has been a renewed interest in modeling the human operator. There has also been significant work on techniques used to identify the pilot model of a given structure. The purpose of this research is to attempt to go beyond pilot identification based on collected experimental data and to develop a predictor of pilot behavior. An experiment was conducted to quantify the effects of changing aircraft dynamics on an operator’s ability to track a signal in order to eventually model a pilot adapting to changing aircraft dynamics. A gradient descent estimator and a least squares estimator with exponential forgetting used these data to predict pilot stick input. The results indicate that individual pilot characteristics and vehicle dynamics did not affect the accuracy of either estimator method to estimate pilot stick input. These methods also were able to predict pilot stick input during changing aircraft dynamics and they may have the capability to detect a change in a subject due to workload, engagement, etc. or the effects of changes in vehicle dynamics on the pilot.