The Underpinnings of Workload in Unmanned Vehicle Systems

This paper identifies and characterizes factors that contribute to operator workload in unmanned vehicle systems. Our objective is to provide a basis for developing models of workload for use in design and operation of complex human-machine systems. In 1986, Hart developed a foundational conceptual model of workload, which formed the basis for arguably the most widely used workload measurement techniquethe NASA Task Load Index. Since that time, however, there have been many advances in models and factor identification as well as workload control measures. Additionally, there is a need to further inventory and describe factors that contribute to human workload in light of technological advances, including automation and autonomy. Thus, we propose a conceptual framework for the workload construct and present a taxonomy of factors that can contribute to operator workload. These factors, referred to as workload drivers, are associated with a variety of system elements including the environment, task, equipment and operator. In addition, we discuss how workload moderators, such as automation and interface design, can be manipulated in order to influence operator workload. We contend that workload drivers, workload moderators, and the interactions among drivers and moderators all need to be accounted for when building complex, human-machine systems

Operator Scheduling Strategies in Supervisory Control of Multiple UAVs

The application of network centric operations to time-constrained command and control environments will mean that human operators will be increasingly responsible for multiple simultaneous supervisory control tasks. One such futuristic application will be the control of multiple unmanned aerial vehicles (UAVs) by a single operator. To achieve such performance in complex, time critical, and high risk settings, automated systems will be required both to guarantee rapid system response as well as manageable workload for operators. Through the development of a simulation test bed for human supervisory control of multiple independent UAVs by a single operator, this paper presents recent efforts to investigate workload mitigation strategies as a function of increasing automation. A humanin- the-loop experiment revealed that under low workload conditions, operators’ cognitive strategies were relatively robust across increasing levels of automated decision support. However, when provided with explicit automated recommendations and with the ability to negotiate with external agencies for delays in arrival times for targets, operators inappropriately fixated on the need to globally optimize their schedules. In addition, without explicit visual representation of uncertainty, operators tended to treated all probabilities uniformly. This study also revealed that operators that reached cognitive saturation adapted two very distinct management strategies, which led to varying degrees of success. Lastly, operators with management-by-exception decision support exhibited evidence of automation bias.This research was sponsored by Boeing Phantom Works

NtoM: a concept of operations for pilots of multiple remotely piloted aircraft

The concept of operations proposed here pursues the feasibility, from a human factors perspective, of having a single pilot/aircrew controlling several remotely piloted aircraft systems at once in non-segregated airspace. To meet such feasibility, this multitasking must be safe and not interfere with the job of the air traffic controllers due to delays or errors associated with parallel piloting. To that end, a set of measures at several levels is suggested, which includes workload prediction and balance, pilot activity monitoring, and a special emphasis on interface usability and the pilot’s situational awareness. The concept relies greatly on the exploitation of the potential of Controller-Pilot Data Link Communications, anticipating future widespread implementation and full use. Experiments comparing the performance of the same pseudo-pilots before and after the implementation of part of the measures showed a decrease in the number of errors, oversights and subjective stress.Peer ReviewedPostprint (published version

A Study on Workload Assessment and Usability of Wind-Aware User Interface for Small Unmanned Aircraft System Remote Operations

This study evaluates pilots' cognitive workload and situational awareness during remote small unmanned aircraft system operations in different wind conditions. To complement the urban air mobility concept that envisions safe, sustainable, and accessible air transportation, we conduct multiple experiments in a realistic wind-aware simulator-user interface pipeline. Experiments are performed with basic and wind-aware displays in several wind conditions to assess how complex wind fields impact pilots' cognitive resources. Post-hoc analysis reveals that providing pilots with real-time wind information improves situational awareness while decreasing cognitive workload

The Effect of Task Load, Automation Reliability, and Environment Complexity on UAV Supervisory Control Performance

Over the last decade, military unmanned aerial vehicles (UAVs) have experienced exponential growth and now comprise over 40% of military aircraft. However, since most military UAVs require multiple operators (usually an air vehicle operator, payload operator, and mission commander), the proliferation of UAVs has created a manpower burden within the U.S. military. Fortunately, simultaneous advances in UAV automation have enabled a switch from direct control to supervisory control; future UAV operators will no longer directly control a single UAV subsystem but, rather, will control multiple advanced, highly autonomous UAVs. However, research is needed to better understand operator performance in a complex UAV supervisory control environment. The Naval Research Lab (NRL) developed SCOUT™ (Supervisory Control Operations User Testbed) to realistically simulate the supervisory control tasks that a future UAV operator will likely perform in a dynamic, uncertain setting under highly variable time constraints. The study reported herein used SCOUT to assess the effects of task load, environment complexity, and automation reliability on UAV operator performance and automation dependence. The effects of automation reliability on participants’ subjective trust ratings and the possible dissociation between task load and subjective workload ratings were also explored. Eighty-one Navy student pilots completed a 34:15 minute pre-scripted SCOUT scenario, during which they managed three helicopter UAVs. To meet mission goals, they decided how to best allocate the UAVs to locate targets while they maintained communications, updated UAV parameters, and monitored their sensor feeds and airspace. After completing training on SCOUT, participants were randomly sorted into low and high automation reliability groups. Within each group, task load (the number of messages and vehicle status updates that had to be made and the number of new targets that appeared) and environment complexity (the complexity of the payload monitoring task) were varied between low and high levels over the course of the scenario. Participants’ throughput, accuracy, and expected value in response to mission events were used to assess their performance. In addition, participants rated their subjective workload and fatigue using the Crew Status Survey. Finally, a four-item survey modeled after Lee and Moray’s validated (1994) scale was used to assess participants’ trust in the payload task automation and their self-confidence that they could have manually performed the payload task. This study contributed to the growing body of knowledge on operator performance within a UAV supervisory control setting. More specifically, it provided experimental evidence of the relationship between operator task load, task complexity, and automation reliability and their effects on operator performance, automation dependence, and operators’ subjective experiences of workload and fatigue. It also explored the relationship between automation reliability and operators’ subjective trust in said automation. The immediate goal of this research effort is to contribute to the development of a suite of domain-specific performance metrics to enable the development and/or testing and evaluation of future UAV ground control stations (GCS), particularly new work support tools and data visualizations. Long-term goals also include the potential augmentation of the current Aviation Selection Test Battery (ASTB) to better select future UAV operators and operational use of the metrics to determine mission-specific manpower requirements. In the far future, UAV-specific performance metrics could also contribute to the development of a dynamic task allocation algorithm for distributing control of UAVs amongst a group of operators

Comparing Types Of Adaptive Automation Within A Multi-tasking Environment

Throughout the many years of research examining the various effects of automation on operator performance, stress, workload, etc., the focus has traditionally been on the level of automation, and the invocation methods used to alter it. The goal of the current study is to instead examine the utilization of various types of automation with the goal of better meeting the operator’s cognitive needs, thus improving their performance, workload, and stress. The task, control of a simulated unmanned robotic system, is designed to specifically stress the operator’s visual perception capabilities to a greater degree. Two types of automation are implemented to support the operator’s performance of the task: an auditory beep aid intended to support visual perception resources, and a driving aid automating control of the vehicle’s navigation, offloading physical action execution resources. Therefore, a comparison can be made between types of automation intended to specifically support the mental dimension that is under the greatest demand (the auditory beep) against those that do not (the driving automation). An additional evaluation is made to determine the benefit of adaptively adjusting the level of each type of automation based on the current level of task demand, as well as the influence of individual differences in personality. Results indicate that the use of the auditory beep aid does improve performance, but also increases Temporal Demand and Effort. Use of driving automation appears to disengage the operator from the task, eliciting a vigilance response. Adaptively altering the level of automation to meet task demands has a mixed effect on performance and workload (reducing both) when the auditory beep automation is used. However, adaptive driving automation is clearly detrimental, iv causing an increase in workload while decreasing performance. Higher levels of Neuroticism are related to poorer threat detection performance, but personality differences show no indication of moderating the effects of either of the experimental manipulations. The results of this study show that the type of automation implemented within an environment has a considerable impact on the operator, in terms of performance as well as cognitive/emotional stat

Influence of Night Work on Performance during Lunar Telerobotic Operations

Real-time, reactive telerobotic mission control operations require personnel to actively operate remotely controlled vehicles or robots in real time. Due to the physical separation of the vehicle from the operator, such operations present additional factors that can influence fatigue (degraded mental performance) and workload (mental and physical cost of task requirements), making it difficult to assess how long an individual can conduct operations safely. The upcoming Volatiles Investigating Polar Exploration Rover will involve remotely controlling a lunar vehicle from an Earth-based mission control station. In order to determine how long personnel could successfully maintain alertness and performance while operating a rover, we studied seven trained operators in a simulated mission control environment. Operators completed two five-hour simulations in a randomized order, beginning at noon and at midnight. Performance was evaluated every 30 minutes using the Psychomotor Vigilance Task (PVT), Karolinska Sleepiness Scale (KSS), and NASA Task Load Index (NASA-TLX). On average, participants rated themselves as sleepier on the midnight drives compared to the day drives. Workload was rated higher during the noon drives compared to midnight. Lastly, participants had no change in average reaction time between the two drives. From the analysis, performance showed degradation after approximately three hours of driving. Our findings suggest that rotating drivers at least every three hours would be prudent to allow for breaks, and to minimize performance degradation, particularly during midnight shifts

AN ANALYSIS OF HOW THE U.S. GOVERNMENT CAN EFFECTIVELY TACKLE SUPPLY CHAIN BARRIERS TO SCALE UP THE LOW COST UNMANNED AERIAL VEHICLE (UAV) SWARMING TECHNOLOGY (LOCUST) PROGRAM

The LOCUST program is a scalable system of inexpensive swarming unmanned aerial vehicles to provide disruptive capability in contested environments against anti-area access denial defenses, enabling manned strike operations and localized landing site superiority with reduced cost, risk, and operator launch and workload. Our research and analysis will emphasize the challenges of moving from a U.S. Special Operations Command (USSOCOM) effort to a large program of record. Specific supply chain concerns that will be addressed include: 1) DOD organizational structure; 2) service-specific objectives and currently operating platforms; 3) requirements generation and related procurements to include production and quality challenges; 4) safety and quality assurance standards; 5) lead times, inventory plans, and throughput to include supplier base considerations and consolidations; and 6) latest evolving technologies and continuous improvement principles. Our team will utilize the Define, Measure, Analyze, Improve, Control (DMAIC) evaluative methodology that focuses on data-driven improvement cycles to better optimize process, design and results. Our results and recommendations highlighted multiple strategies that the Office of Naval Research (ONR) must focus on when developing the LOCUST supply chain. These conclusions and findings address both current supply chain development opportunities for the LOCUST program, as well as where the program must focus its efforts in the future.http://archive.org/details/ananalysisofhowt1094563516Civilian, Department of the NavyCivilian, Department of the ArmyCivilian, Department of the ArmyApproved for public release; distribution is unlimited