Flight Deck Surface Trajectory-Based Operations (STBO): A Four-Dimensional Trajectory (4DT) Simulation

In four-dimensional trajectory (4DT) Surface Trajectory-Based Operations (STBO), aircraft are assigned a conflict-free 4DT which defines an expected location (x,y coordinates) at all times, t, along the taxi route (with altitude, being fixed). These 4DTs afford the highest temporal certainty at all points along the taxi route, and at the departure runway. In the present study, a 4DT flight deck display was presented on the Airport Moving Map (AMM) to support pilot conformance to a 4DT clearance while taxiing under manual control. This pilot-in-the-loop simulation compared the effect of 4DT flight deck display formats on distance from the expected 4DT location, conformance to the displayed tolerance band, eyes-out time, and pilot ratings of safety and workload. In the defined-tolerance display format, a graphical representation of the expected 4DT location, with a distance-based allowable-tolerance band, was depicted on the AMM. Two defined-tolerance band sizes were tested: plus or minus 164 feet and plus or minus 405 feet. In the undefined-tolerance display format, the expected 4DT location was displayed graphically on the AMM, with no indicated allowable-tolerance bounds. Each taxi trial included 4DT speed changes (two or five, per trial) and a range of 4DT taxi speeds. Results showed that the larger (plus or minus 405 feet) defined-tolerance band yielded higher conformance levels than the smaller (plus or minus 164 feet) band, with pilots staying within the specified and displayed conformance bounds more in the larger (99.71%) than the smaller defined-tolerance band (93.37 percent). However, in terms of being able to predict the location of the aircraft compared to the expected 4DT location, the smaller defined-tolerance band resulted in pilots keeping their aircraft closer to the 4DT location, for both average distance and for a given confidence interval (e.g., 95 percent), than either the larger defined-tolerance band or the undefined-tolerance display format. The larger tolerance band yielded more eyes-out-the-window time than the smaller tolerance band. Pilots also rated taxing with the larger tolerance band as safer than the smaller tolerance band

ATD-2 Integrated Arrival, Departure, and Surface (IADS) Operations

The ATD-2 Integrated Arrival, Departure, and Surface (IADS) traffic management system extends integrated traffic sequencing all the way from the gate to the overhead stream and back again for multi-airport, metroplex environments. NASA and the FAA are developing the IADS system in close coordination with industry partners

A Concept of Operations for Far-Term Surface Trajectory-Based Operations (STBO)

The goal of this far-term STBO (Surface Trajectory-Based Operations) ConOps (Concept of Operations) is to increase the efficiency and predictability of airport surface operations, and reduce the environmental impact, by incorporating a time-based component to surface operations. In the far-term NextGen timeframe, airport surface operations will transition from current-day first-come, first-served operations, to strategically scheduled operations in which pilots are recruited as active participants in meeting the precise time-based goals of NextGen surface operations. The far-term STBO concept includes two-phases. Phase 1 introduces time-based traffic flow constraint points, which divide the taxi route into segments with an assigned Required Time of Arrival (RTA). This Phase 1 approach provides temporal certainty only near the traffic flow constraint points, but not in between. Minimal augmentations to the flight deck are required to support required time of arrival (RTA) management. Phase 2 further increases precision and efficiency by introducing full four-dimensional (4D) trajectories, with an x-y location for all times t. This phase assumes adoption of advanced flight deck equipage enabling higher temporal precision sufficient to support aircraft conformance to 4D trajectories. This allows more precision and less temporal uncertainty at all times along the route

Flight Deck Surface Trajectory-based Operations (STBO): Results of Piloted Simulations and Implications for Concepts of Operation (ConOps)

The results offour piloted medium-fidelity simulations investigating flight deck surface trajectory-based operations (STBO) will be reviewed. In these flight deck STBO simulations, commercial transport pilots were given taxi clearances with time and/or speed components and required to taxi to the departing runway or an intermediate traffic intersection. Under a variety of concept of operations (ConOps) and flight deck information conditions, pilots' ability to taxi in compliance with the required time of arrival (RTA) at the designated airport location was measured. ConOps and flight deck information conditions explored included: Availability of taxi clearance speed and elapsed time information; Intermediate RTAs at intermediate time constraint points (e.g., intersection traffic flow points); STBO taxi clearances via ATC voice speed commands or datal ink; and, Availability of flight deck display algorithms to reduce STBO RTA error. Flight Deck Implications. Pilot RTA conformance for STBO clearances, in the form of ATC taxi clearances with associated speed requirements, was found to be relatively poor, unless the pilot is required to follow a precise speed and acceleration/deceleration profile. However, following such a precise speed profile results in inordinate head-down tracking of current ground speed, leading to potentially unsafe operations. Mitigating these results, and providing good taxi RTA performance without the associated safety issues, is a flight deck avionics or electronic flight bag (EFB) solution. Such a solution enables pilots to meet the taxi route RTA without moment-by-moment tracking of ground speed. An avionics or EFB "error-nulling" algorithm allows the pilot to view the STBO information when the pilot determines it is necessary and when workload alloys, thus enabling the pilot to spread his/her attention appropriately and strategically on aircraft separation airport navigation, and the many other flight deck tasks concurrently required. Surface Traffic Management (STM) System Implications. The data indicate a number of implications regarding specific parameters for ATC/STM algorithm development. Pilots have a tendency to arrive at RTA points early with slow required speeds, on time for moderate speeds, and late with faster required speeds. This implies that ATC/STM algorithms should operate with middle-range speeds, similar to that of non-STBO taxi performance. Route length has a related effect: Long taxi routes increase the earliness with slow speeds and the lateness with faster speeds. This is likely due to the" open-loop" nature of the task in which the speed error compounds over a longer time with longer routes. Results showed that this may be mitigated by imposing a small number oftime constraint points each with their own RTAs effectively tuming a long route into a series of shorter routes - and thus improving RTA performance. STBO ConOps Implications. Most important is the impact that these data have for NextGen STM system ConOps development. The results of these experiments imply that it is not reasonable to expect pilots to taxi under a "Full STBO" ConOps in which pilots are expected to be at a predictable (x,y) airport location for every time (t). An STBO ConOps with a small number of intermediate time constraint points and the departing runway, however, is feasible, but only with flight deck equipage enabling the use of a display similar to the "error-nulling algorithm/display" tested

Flight-Deck Surface Trajectory-Based Operations

The results of three piloted simulations investigating flight-deck surface trajectory-based operations (STBO) are presented. Commercial transport pilots were given taxi clearances with time and speed components on the primary flight display and were required to taxi to the departing runway or intermediate intersections. Results show that when pilots were provided with speed-only taxi clearances, pilots either had poor required time of arrival (RTA) conformance with acceptable estimates of attentional distribution and safety, or had good RTA conformance with unacceptable attentional distribution and safety estimates. A flight-deck error-nulling algorithm/display allowed pilots to conform accurately with taxi RTA clearances while maintaining safety. Results are discussed in terms of pilot multitasking in the busy airport surface operations environment

DataComm in Flight Deck Surface Trajectory-Based Operations

The purpose of this pilot-in-the-loop aircraft taxi simulation was to evaluate a NextGen concept for surface trajectory-based operations (STBO) in which air traffic control (ATC) issued taxi clearances with a required time of arrival (RTA) by Data Communications (DataComm). Flight deck avionics, driven by an error-nulling algorithm, displayed the speed needed to meet the RTA. To ensure robustness of the algorithm, the ability of 10 two-pilot crews to meet the RTA was tested in nine experimental trials representing a range of realistic conditions including a taxi route change, an RTA change, a departure clearance change, and a crossing traffic hold scenario. In some trials, these DataComm taxi clearances or clearance modifications were accompanied by preview information, in which the airport map display showed a preview of the proposed route changes, including the necessary speed to meet the RTA. Overall, the results of this study show that with the aid of the RTA speed algorithm, pilots were able to meet their RTAs with very little time error in all of the robustness-testing scenarios. Results indicated that when taxi clearance changes were issued by DataComm only, pilots required longer notification distances than with voice communication. However, when the DataComm was accompanied by graphical preview, the notification distance required by pilots was equivalent to that for voice

Flight Deck Surface Trajectory-Based Operations (STBO): A Four-Dimensional Trajectory (4DT) Simulation

Within human factors there is burgeoning interest in the Human-Autonomy Teaming (HAT) concept as away to address the challenges of interacting with complex, increasingly autonomous systems. The HAT concept comes out of an aspiration to interact with increasingly autonomous automation as a team member, rather than simply use automation as a tool. The authors, and others, have proposed core tenets for HAT that include bi-directional communication, automation and system transparency, and advanced coordination between human and automated teammates via predefined, dynamic task sequences known as plays (Shively et al., 2017). It is believed that, with proper implementation, HAT should foster appropriate teamwork, thus increasing trust and reliance on the system, which in turn will reduce workload, increase situation awareness, and improve performance. To this end, HAT has been demonstrated and/or studied in multiple applications including search and rescue operations (Nourbakhsh et al., 2005), healthcare and medicine (Tsui Yanco, 2007), autonomous vehicles (Parasuraman, Barnes, Cosenzo, Mulgund, 2007), photography (Lachter, Brandt, Sadler, Shively, in press), and aviation (Shively et al., in press). The current paper presents one such effort to apply HAT. It details the design of a R-HAT Agent developed as part of a NASA Research Agreement awarded to Human-Autonomy Teaming Solutions Inc. (HATS Inc), and developed in collaboration with the Human-Autonomy Teaming Laboratory at NASA Ames Research Center. The role of this Agent is to mediate interaction between the automation and the human operator of an advanced ground dispatch station, with this mediation based upon previously mentioned core tenets for HAT and the many lessons learned from the HAT research literature. This dispatch station was developed to support a NASA project investigating a concept called Reduced Crew Operations (RCO; Lachter, Brandt, Battiste, Matessa, Johnson, in press). Part of the RCO concept involves a ground operator providing enhanced support to a large number of aircraft with a single pilot on the flight deck. When assisted by the Agent, operators can monitor and support or manage a large number of aircraft and use plays to respond in real-time to complicated, workload-intensive events (e.g., an airport closure). A play is a plan that encapsulates goals, tasks, and a task allocation strategy appropriate for a particular situation. In the current implementation, when a play is initiated by a user, the Agent determines what tasks need to be done and has the ability to autonomously execute them (e.g., determining diversion options and uplinking new routes to aircraft) when it is safe and appropriate. The R-HAT Agent has been designed to both support end users and research in RCO and HAT. Additionally, the Agent and its underlying architecture were developed with generalizability in mind as a modular piece of software applicable outside of RCO aviation in domains such as those mentioned above. This paper will also discuss future further development and testing of the R-HAT Agent

Flight Deck Surface Trajectory-Based Operations

Surface Trajectory-Based Operations (STBO) is a future concept for surface operations where time requirements are incorporated into taxi operations to support surface planning and coordination. Pilot-in-the-loop flight deck simulations have been conducted to study flight deck displays algorithms to aid pilots in complying with the time requirements of time-based taxi operations (i.e., at discrete locations in 3 12 D operations or at all points along the route in 4DT operations). The results of these studies (conformance, time-of-arrival error, eye-tracking data, and safety ratings) are presented. Flight deck simulation work done in collaboration with DLR is described. Flight deck research issues in future auto-taxi operations are also introduced

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

Predicting the Unpredictable: Estimating Human Performance Parameters for Off-Nominal Events

A parameter meta-analysis was conducted to characterize human responses to off-nominal events. The probability of detecting an off-nominal event was influenced by characteristics of the offnominal event scenario (phase of flight, expectancy, and event location) and the presence of advanced cockpit technologies (head-up displays, highway-in-the-sky displays, datalink, and graphical route displays). The results revealed that the presence of these advanced technologies hindered event detection reflecting cognitive tunneling and pilot complacency effects