Potential applications include HMD use in which head position is tracked and visual imagery is linked to head or body movement, such as in virtual and augmented reality systems, and is thus critical to functionality and performance.

The integration of Unmanned Aircraft Systems (UAS) into the National Airspace System (NAS) requires that UAS meet or exceed the safety requirements established for conventional aircraft, and for the UAS pilots to interact with air traffic controllers (ATCos) in an acceptable manner.UAS have several characteristics that differentiate them from conventional aircraft, including the possibility of greater latencies associated with remote pilot communication and command execution. The goal of the present study was to determine how adding delays to UAS pilot communications and command executions affect ATCos' interactions with UAS and conventional aircraft. Six previously certified radar controllers and two currently certified radar controllers were recruited as participants to manage traffic in a simulated sector with conventional traffic and one UAS flying in it. The UAS pilot verbal communication and execution latencies were varied in separate scenarios to include an additional delay that was either short (1.5 s) or long (5 s), and constant or variable within each scenario. We measured both UAS and conventional pilots' verbal communication and execution initiation latencies, and obtained ATCos' acceptability ratings for the different delay conditions. Also examined were the number of communication step-ons created by the additional communication delays implemented in the UAS control station, as well as other measures of the ATCo-pilot interactions. We found ATCos rated UAS pilot verbal communication latencies to be acceptable when the latencies were short rather than long and that acceptability ratings often reflect broader features of the sectors being managed. Implications of these findings for UAS integration in the NAS and limitations of the present study are discussed.

The ability of helmet mounted display (HMD) systems to increase effectiveness in operational aircraft has been well documented over the last several years. Now that advanced aircraft are committed to using HMDs in combat operations, issues associated with their use in simulators must be addressed. A major factor associated with the onset of simulator sickness is system latency. Simulator sickness can be a significant distraction during training and may result in ineffective training, negative training, reduced user acceptance, and a reduction in simulator usage. Innovative solutions to address system latency, as well as many other issues, must be developed so that training can be optimized. The current project developed a number of innovative strategies that effectively mitigate both system latency and image alignment error. The strategies developed include: 1) a customized Kalman predictive filter, 2) a learning neural network, and 3) "Warper Board" technology. These strategies operate independently yet in concert to continually sample, compare, and adjust their outputs to produce the most accurate prediction of future image placement possible using current available head movement and position data. Experimental results indicate that effective system latency was reduced up to 90% from the baseline system state. Implications for training systems and improved training will be discussed.

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 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.

In the National Airspace System (NAS), Air Traffic Control (ATC) expects aircraft to complete ATC clearances in a timely manner in order to maintain minimum separation between aircraft. The end-to-end response time for an aircraft to complete a clearance, as measured from the end of ATC instructing the pilot of the clearance to the just noticeable difference (JND) on the ATC display of the aircraft satisfying the clearance (i.e., initiation/completion of an altitude climb), can be referred to as measured response (MR). This MR is not quantified in Federal Aviation Administration (FAA) standards, regulations, or policy; however, as manned aircraft have developed along with the Air Traffic Management System, a shared understanding of reasonable and timely response has evolved. By contrast, the introduction of unmanned aircraft systems (UAS) into the NAS has highlighted this issue. This paper seeks to define MR and its components, and describe a methodology, with an example, that can be used to investigate it.