EFVS Effects on Pilot Performance

Flight tests have been conducted at Purdue University using a computer-based flying simulator in an attempt to determine and measure the effects of Enhanced Flight Vision Systems (EFVS) on the performance of pilots during landing. Knowledge of these effects could help guide future design and implementation of EFVS in modern commercial aircraft, and further increase pilots’ ability to control the aircraft in low-visibility conditions. The problem that has faced researchers in the past has revolved around the difficulty in interpreting the data which is generated by these tests. The difficulty in making a generalized conclusion based on the large amount of data containing various increases, decreases, and absences of difference has led to many either contradicting or inconclusive results. A close look was taken at previously obtained sets of data in order to potentially discover any new statistically significant correlations between the use of EFVS and pilot performance. The data included multiple sets detailing errors, deviations, and eye fixation. Results of these tests were summarized in order to look for patterns in the data which indicated a distinct difference between flying with and without EFVS. Most tests failed to find a correlation, but there was a higher frequency of a test finding or almost finding a statistically significant difference when testing the standard deviation of a sample of measurements than when testing the sample means. These results suggest that, with further testing, a connection between EFVS use and the variance of measurements of pilot performance could potentially be discovered

Pilot Performance with Advance Sensor Technlogies Considerations

Research on human performance indicates people may discretely shift modes as the difficulty in tasks changes. These modes are referred to as “cognitive control modes.” Cognitive control modes are ways people operate and handle their process of thinking during a series of tasks. However, past work has been confined to subjective reports of these mode changes - objective markers in data of cognitive control modes, which should appear if these mode changes are truly discrete, have not be identified. This work will attempt to identify markers of cognitive control modes in data collected on pilots flying instrument approaches. Specifically, a simulated flight experiment is being conducted in which control movement, aircraft state, and eye movement data is being collected. If there are markers of discrete cognitive control mode changes, it should appear in one or more of these sources of data. Finding markers of cognitive control mode changes would provide future research with objective evidence rather than subjective reports on such changes. Being able to rely on objective evidence, rather than subjective evidence, is crucial due to reliability and experimental issues with subjective reports

Dimensions of Pilot Experience and their Contribution to Adverse Weather Decision Making

Erroneous decisions made by pilots during encounters with adverse weather is often cited as a cause of General Aviation accidents. Pilot experience, which can be measured in several ways, is believed to play a role in the outcome of such encounters. However, it is unclear whether any of the elements of experience alone or in combinations affect the likelihood of General Aviation accidents during actual encounters with adverse weather, or how they do so. One barrier to conclusively determining such effects is the danger in extrapolating simulation results to the real world; nearly all work done to date has used simulators to identify accident risk. Therefore, the extent to which such results can be applied to actual flying is not clear. In this work, two conceptual models for analyzing experience and its role in encounters with adverse weather during the cruise phase of General Aviation Part 91 fixed wing operations are presented. A novel method for evaluating accident risk, specifically the likelihood that an incident turns into an accident is also presented and then used to evaluate the experience profile of 595 pilots, detailed in actual accident and incident reports from the NTSB and ASRS databases. The effect of various elements of experience, alone and in combinations, on that risk is evaluated using regression modeling. The level of significance for each experience variable is first established, and then a series of discrete models is developed to progressively evaluate accident risk along a hypothetical experience continuum. This approach obviates commonly encountered challenges with research in the area and provides results that are ecologically valid. The focus of this research work was on the role of cognitive aspects of experience in the outcome of flights during the cruise phase of General Aviation Part 91 fixed wing flights between January 1, 2005 and December 31, 2015. Only flights which encountered adverse weather during the cruise phase and for which experience and/or errors in decision making were determined to be a cause or factor in the outcome were included in the study. All flights during the period that involved takeoff and landing, equipment failure or student pilots were not considered for the study. The emphasis of the research was on the effect of experience on cognitive aspects of pilot performance during adverse weather encounters, rather than “stick and rudder” skills. It was found that variables related to the breadth or variety of pilots’ experience are more predictive of the likelihood of adverse weather encounters turning into accidents compared to those related to the duration or length of experience. While several commonly used measures of experience provide some level of insulation against accidents, the relationship between elements that define the length or duration of experience and outcomes is not linear. Furthermore, this relationship is mediated by variables that define the breadth of experience, especially at their lower levels. These findings may be leveraged to design specifically targeted regulatory or training policies and interventions to expedite the transition from novice to expert pilots in General Aviation weatherrelated decision making

Dimensions of Pilot Experience and Their Contributing Variables

Pilot experience is generally recognized as an insulating factor against erroneous weather-related decision making in General Aviation (GA). A pilot’s level of experience is traditionally taken to correspond to the total flight hours accrued. However, there is some evidence from aviation accident databases and research that total flight hours on its own, may be an inadequate measure of pilot experience. Indeed, pilot experience may be viewed as a multidimensional attribute, with each dimension made up of several elements or variables. How individual elements align with different dimensions, or the extent to which each dimension or the elements thereof contribute to good judgement and aeronautical decision making during adverse weather encounters is unclear. This paper reports initial results from research work carried out to evaluate the extent to which total flight hours and other flight hour related experience variables are associated with the outcome of pilots’ in-flight encounters with adverse weather

Impact of Weather Information Latency on General Aviation Pilot Situation Awareness

A critical element of situation awareness and sensemaking support for humans in complex environments is the ability to access, detect, and integrate environmental elements to recognize and project the state of the world. Some past research has suggested that new weather technology capabilities in general aviation (GA) flight settings could help improve pilot decision making and reduce accidents such as unintentional transitions from visual flight rules (VFR) to marginal VFR or even instrument meteorological conditions (IMC). This paper addresses an ongoing Federal Aviation Administration (FAA) funded research project investigating the effect of transmission delays and update latencies in presentations of weather information to pilots in the GA environment. Across a range of fixed-install, portable, and handheld (i.e. tablet, smartphone) weather information technologies, latencies of up to 15-20 minutes can be identified. These latencies may affect the use of information regarding dangerous weather conditions and timelines of pilot planning activities during VFR-to-IMC transitions