11-19 of 19 results
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An Investigation of Factors that Influence Passengers’ Intentions to Use Biometric Technologies at Airports
PI Kabir Kasim
CO-I Scott Winter
This research investigated the factors that influence passengers’ intentions to choose the use of biometrics over other methods of identification. The current study utilized a quantitative research method via an online survey of 689 persons from Amazon ® Mechanical Turk ® (MTurk) and employed structural equation modeling (SEM) techniques for data analysis. The study utilized the theory of planned behavior (TPB) as the grounded theory, while perceived usefulness and perceived ease of use were included as additional factors that could influence individuals’ intentions to use new technology.
The study further assessed the impact of passengers’ privacy concerns on the intentions to use biometrics and investigated how the privacy concerns moderate the influencing factors of passengers’ behavioral intentions. Because of the coronavirus (COVID-19) pandemic that became prevalent at the time of the study, a COVID-19 variable was introduced as a control variable to examine if there were any effects of COVID-19 on passengers' behavioral intentions while controlling for the other variables.
Results showed that for the TPB factors, attitudes and subjective norms significantly influenced passengers’ behavioral intentions to use biometrics, while the effect of perceived behavioral control (PBC) on passengers’ intentions was not significant. The additional factors of perceived usefulness and perceived ease of use did not significantly influence passengers’ intentions. In addition, the hypothesized relationships between privacy concerns and four factors, behavioral intentions, attitudes, PBC, and perceived ease of use were supported, while the relationships between privacy concerns and perceived usefulness and between privacy concerns and subjective norms were not supported.
The examination of the moderating effects found that privacy concerns moderated the relationships between passengers’ intentions and three factors: attitudes, subjective norms, and perceived usefulness. However, because the interaction plots showed that the moderating effects were weak, the effects were not considered to be of much value and were therefore not added to the final model. Results also showed that the control variable (COVID-19) did not significantly influence passengers’ behavioral intentions and passengers’ privacy concerns while controlling for the other variables.
Practically, the study contributed a research model and specified factors that were postulated to influence passengers’ behavioral intentions to use biometrics at airports. Further research would be required to determine additional factors that influence behavioral intentions. Finally, although the moderating effects were not used in the final model, the findings suggest that stakeholders can customize biometric systems and solutions appropriately to cater to passengers’ concerns.
Categories: Graduate
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The Effects of Carry-on Baggage on Aircraft Evacuation Efficiency
PI Sang-A Lee
Overall, two studies were conducted to provide an outline of the factors that affect and affected by carry-on baggage. Study 1 used an agent-based model, AnyLogic, to simulate the aircraft evacuation model of an A380. The model was validated, and a two-way Analysis of Variance (ANOVA) was conducted to examine the effects of the percentage of passengers evacuating with carry-on baggage and exit selection choices on the total evacuation time. The simulation results suggested that the mean evacuation time for 0% was significantly lower than 50% and 80%. The mean evacuation time for the shortest queue choice was also lower than the closest exit choice. Study 2 used an expanded theory of planned behavior (TPB) to determine the factors that affect passengers’ intentions to evacuate with carry-on baggage. The confirmatory factor analysis (CFA) and structural equation model (SEM) were used to analyze the data. The results indicated that attitude was the significant determinant of passengers’ intention to evacuate with carry-on baggage.
The most frequent obstacle of an aircraft evacuation is the passengers carrying baggage while evacuating. Passengers who insist on taking their carry-on baggage during an emergency evacuation not only slow down the evacuation process but also act as a significant risk to the safety of other passengers. This study investigated the factors that affect passengers’ behavioral intention to evacuate with carry-on baggage and the effects of evacuating with carry-on baggage on the total evacuation time. Overall, two studies were conducted to provide an outline of the factors that affect and affected by carry-on baggage.
Study 1 used an agent-based model, AnyLogic, to simulate the aircraft evacuation model of an A380. The model was validated, and a two-way Analysis of Variance (ANOVA) was conducted to examine the effects of the percentage of passengers evacuating with carry-on baggage and exit selection choices on the total evacuation time. The simulation results suggested that the mean evacuation time for 0% was significantly lower than 50% and 80%. The mean evacuation time for the shortest queue choice was also lower than the closest exit choice.
Study 2 used an expanded theory of planned behavior (TPB) to determine the factors that affect passengers’ intentions to evacuate with carry-on baggage. The total v sample size was 281 after data cleaning. The confirmatory factor analysis (CFA) and structural equation model (SEM) were used to analyze the data. The results indicated that attitude was the significant determinant of passengers’ intention to evacuate with carry-on baggage. The factor of ‘perceived risk’ was not supported, but the results showed that the opposite effect of the hypothesis was significant. The results of this study fill a gap in the research regarding passengers’ behavior of evacuating with carry-on baggage. Potential applications of this study will also help the federal regulations, airlines, and aircraft manufacturers by providing a better understanding of carry-on baggage at aircraft emergency.
Categories: Graduate
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Predicting Pilot Misperception of Runway Excursion Risk Through Machine Learning Algorithms of Recorded Flight Data
PI Edwin Odisho
CO-I Dothang Truong
The research used predictive models to determine pilot misperception of runway excursion risk associated with unstable approaches. The Federal Aviation Administration defined runway excursion as a veer-off or overrun of the runway surface. The Federal Aviation Administration also defined a stable approach as an aircraft meeting the following criteria: (a) on target approach airspeed, (b) correct attitude, (c) landing configuration, (d) nominal descent angle/rate, and (e) on a straight flight path to the runway touchdown zone. Continuing an unstable approach to landing was defined as Unstable Approach Risk Misperception in this research. A review of the literature revealed that an unstable approach followed by the failure to execute a rejected landing was a common contributing factor in runway excursions.
Flight Data Recorder data were archived and made available by the National Aeronautics and Space Administration for public use. These data were collected over a four-year period from the flight data recorders of a fleet of 35 regional jets operating in the National Airspace System. The archived data were processed and explored for evidence of unstable approaches and to determine whether or not a rejected landing was executed. Once identified, those data revealing evidence of unstable approaches were processed for the purposes of building predictive models.
SAS™ Enterprise MinerR was used to explore the data, as well as to build and assess predictive models. The advanced machine learning algorithms utilized included: (a) support vector machine, (b) random forest, (c) gradient boosting, (d) decision tree, (e) logistic regression, and (f) neural network. The models were evaluated and compared to determine the best prediction model. Based on the model comparison, the decision tree model was determined to have the highest predictive value.
The Flight Data Recorder data were then analyzed to determine predictive accuracy of the target variable and to determine important predictors of the target variable, Unstable Approach Risk Misperception. Results of the study indicated that the predictive accuracy of the best performing model, decision tree, was 99%. Findings indicated that six variables stood out in the prediction of Unstable Approach Risk Misperception: (1) glideslope deviation, (2) selected approach speed deviation (3) localizer deviation, (4) flaps not extended, (5) drift angle, and (6) approach speed deviation. These variables were listed in order of importance based on results of the decision tree predictive model analysis.
The results of the study are of interest to aviation researchers as well as airline pilot training managers. It is suggested that the ability to predict the probability of pilot misperception of runway excursion risk could influence the development of new pilot simulator training scenarios and strategies. The research aids avionics providers in the development of predictive runway excursion alerting display technologies.
Categories: Graduate
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Pilot Acceptance of Personal, Wearable Fatigue Monitoring Technology: An Application of the Extended Technology Acceptance Model
PI Rachelle Strong
CO-I Dahai Liu
The research problem of pilot fatigue has been referenced as a causal factor for aircraft accidents in many United States National Transportation and Safety Board (NTSB) accident reports; however, the United States Code of Federal Regulations 14 CFR Part 117, Flight and Duty Limitations and Rest Requirements for Flight Crew Members, does not provide a tangible means of measuring fatigue for aircraft crew members. This problem is relevant to the airline industry and the travelling public because pilot fatigue is preventable as a causal factor in aviation accidents, and pilots need an accurate way to measure it. Adoption of a technology-based solution has been recommended by the NTSB.
The purpose of this study was to determine the factors that affect United States certified airline transport pilots’ behavioral intention to use personal, wearable fatigue monitoring technology (FMT), such as a Fitbit or Apple Watch, to assess their personal fatigue levels. FMT could potentially be used to help meet pilots’ legal requirement to be aware of their personal fatigue levels, per 14 CFR Part 117. The theoretical framework for this study is the Extended Technology Acceptance Model, and the research question is: What factors affect pilots’ behavioral intention to use personal, wearable fatigue monitoring technology, and to what degree? There were ten hypotheses tested that corresponded to different relationships in the model.
The data for this study was collected using an online survey distributed to certified airline transport pilots in the United States, in which the survey questions corresponded to observed variables pertaining to each of the eight factor constructs in the model. The data was analyzed using confirmatory factor analysis (CFA) and structural equation modeling (SEM) techniques to test the hypotheses. The results of the study contributed to the theoretical body of knowledge by demonstrating that a modified version of the Extended Technology Acceptance Model was applicable to U.S. airline transport pilot behavioral intention to use FMT. Six of the ten original hypotheses were supported, and four were not supported.
It was determined that the primary factors that positively affect a pilot’s behavioral intention to use FMT are perceived usefulness and perceived ease of use. Perceived usefulness is positively affected by the external factors of job relevance, results demonstrability, and perceived image or social status, which act as secondary factors positively influencing behavioral intention to use FMT. A tertiary factor influencing behavioral intention to use FMT is subjective norms, which positively influence perceived image, thus positively affecting perceived usefulness and intention to use FMT. Output quality, subjective norms, and perceived ease of use were determined to not have a statistically significant effect on pilots’ perceived usefulness of FMT, and subjective norms were determined not to have a statistically significant effect on pilots’ behavioral intention to use FMT.
The practical significance of this study is that pilots find FMT devices most useful when it is applicable to their jobs, provides tangible results, and increases their social status perception. It is beneficial if others around them think they should use FMT, and that if they use FMT, their social status perception increases. Practical solutions to increase the likelihood of pilot FMT device usage should include wearable device applications that provide features that directly apply to the pilot profession, report data in ways that make sense to pilots, and also make the pilot look and feel stylish. Nearly 87 percent of pilots already wear a watch while flying, and over 40 percent of pilots already wear some form of FMT for personal use, so the challenge going forward is to make the right improvements to the devices to increase usage. Such improvements may include new aviation-themed applications that appeal to pilots and provide results that can help them make more informed decisions, while simultaneously improving the aesthetic to drive an increase in social pressures to wear the FMT devices regularly.
Categories: Graduate
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The Effects of Remotely Piloted Aircraft Command and Control Latency during Within-Visual-Range Air-To-Air Combat
PI David Thirtyacre
CO-I David Cross
The type of military missions conducted by remotely piloted aircraft continues to expand into all facets of operations including air-to-air combat. While future within-visual-range air-to-air combat will be piloted by artificial intelligence, remotely piloted aircraft will likely first see combat. The purpose of this study was to quantify the effect of latency on one-versus-one, within-visual-range air-to-air combat success during both high-speed and low-speed engagements. The research employed a repeated-measures experimental design to test the various hypothesis associated with command and control latency. Participants experienced in air-to-air combat were subjected to various latency inputs during one-versus-one simulated combat using a virtual-reality simulator and scored on the combat success of each engagement. This research was pursued in coordination with the Air Force Research Laboratory and the United States Air Force Warfare Center.
The dependent variable, combat score, was derived through post-simulation analysis and scored for each engagement. The independent variables included the input control latency (time) and the starting velocity of the engagement (high-speed and low-speed). The input latency included six different delays (0.0, 0.25, 0.50, 0.75, 1.0, and 1.25 seconds) between pilot input and simulator response. Each latency was repeated for a high-speed and low-speed engagement. A two-way repeated-measures analysis of variance was used to determine whether there was a statistically significant difference in means between the various treatments on combat success and determine if there was an interaction between latency and fight speed.
The results indicated that there was a statistically significant difference between combat success at the various latency levels and engagement velocity. There was a significant interaction effect between latency and engagement speed, indicating that the outcome was dependent on both variables. As the latency increased, a significant decrease in combat success occurred, decreasing from .539 with no latency, to .133 at 1.250 seconds of latency during high-speed combat. During low-speed combat, the combat success decreased from .659 with no latency, to .189 at 1.250 seconds of latency. The largest incremental decrease occurred between 1.00 and 1.25 seconds of latency for high-speed and between 0.75 and 1.00 at low-speed. The overall decrease in combat success during a high-speed engagement was less than during the low-speed engagements.
The results of this study quantified the decrease in combat success during within-visual range air-to-air combat and concluded that, when latency is encountered, a high-speed (two-circle) engagement is desired to minimize adverse latency effects. The research informs aircraft and communication designers of the decrease in expected combat success caused by latency. This simulation configuration can be utilized for future research leading to methods and tactics to decrease the effects of latency.
Categories: Graduate
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Pilot’s Willingness to Operate in Unmanned Aircraft System Integrated Airspace
PI Lakshmi Vempati
PI Scott Winter
The interest in Unmanned Aircraft Systems (UAS) use for private, civil, and commercial purposes such as package delivery, inspection, surveillance, and passenger and cargo transport has gained considerable momentum. As UAS infiltrate the National Airspace System (NAS), there is a need to not only develop viable, safe, and secure solutions for the co-existence of manned and unmanned aircraft, but also determine public acceptance and pilot’s willingness to operate an aircraft in such an integrated environment. Currently there is little or no research on pilot’s perceptions on their willingness to operate an aircraft in UAS integrated airspace and airports.
The purpose of this study was to determine what effect the type of UAS integration, the type of UAS operations, and the airspace classification will have on pilot’s perspectives and willingness to operate an aircraft in UAS integrated airspace and airport environment. This study surveyed the eligible pilot population in hypothetical scenarios using convenience sampling to measure their willingness to operate an aircraft in UAS integrated airspace and airports using the Willingness to Pilot an Aircraft Scale, which has been shown to be valid and reliable by Rice, Winter, Capps, Trombley, Robbins, and Milner (2020). A mixed factorial design was used to study the interaction effects between the independent variables and the effects on the dependent variable, i.e., willingness to pilot an aircraft.
The results of the mixed analysis of variance (ANOVA) indicated a significant interaction between type of UAS integration and airspace classification. Overall willingness decreased with airspace and differences in willingness to pilot an aircraft were based on segregated and integrated operations. The average pilot’s willingness to pilot an aircraft score differed from the highest score being for Class B, decreasing with decreasing airspace classes, with the lowest being for Class G.
Analysis of pilot perspectives collected through open ended questions using text-mining techniques showed agreement with mixed ANOVA analysis that the primary factor in the pilot’s perception was airspace. Key concerns voiced by the pilots were situation awareness, risk and safety of operations, aircraft certification and airworthiness, and operator experience and regulatory conformance. The most positive sentiment was observed among pilots presented with the hypothetical scenario of fully autonomous UAS operations in a segregated environment. Findings from the study could aid regulators in developing better policies, procedures, integration solutions, improved training, and knowledge sharing.
Categories: Graduate
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Air Traffic Controllers’ Occupational Stress and Performance in the Future Air Traffic Management
PI Hui Wang
CO-I Edward Mummert
As demand for unmanned aerial vehicle (UAV) operations increases, it is vital to understand its effects on air traffic controllers and the safety of the national airspace system. This study’s primary purpose is to determine how UAVs that operate in controlled airspace would influence air traffic controllers’ occupational stress and performance. In a within-subject experimental research design, 24 participants sampled from a university’s undergraduate Air Traffic Management (ATM) program completed three different air traffic control (ATC) scenarios on an en-route ATC simulation system. The degree of UAV automation and control were varied in each scenario. The participants’ stress levels, performance, and workload were measured with both objective and subjective measurements. Within-subjects ANOVA tests showed significant effects on the participants’ stress level, performance, and workload when automated UAVs were present in the scenario. Participants experienced increased workload, the highest level of stress, and carried out the worst performance when with controllable UAVs in the airspace. These findings can inform UAV integration into controlled airspace and future research into UAV automation and control and ATC management.
Categories: Graduate
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Safety Systems, Culture, and Passengers’ Willingness to Fly in Autonomous Air Taxis
PI Kenneth Ward
CO-I Scott Winter
As city populations grow, the transportation industry plans to alleviate traffic congestion by introducing the urban air mobility (UAM) concept, in which small passenger and cargo aircraft augment metropolitan transportation networks. A key component of UAM is that of air taxis, which are on-demand air services for individuals and small groups. In addition, UAM companies are designing the aircraft to operate fully autonomously: The intent is for the vehicles to arrive and transport people from point to point without input from human pilots.
In studies of passengers’ perceptions, researchers found that safety was among the top passenger concerns. The international market complicates the matter, as research indicates people from different nations differ in their willingness to fly in autonomous aircraft. Past research hypothesized that individuals’ cultural orientation, specifically their degree of individualism or communalism, was a factor of the differences in willingness to fly.
A quantitative survey experiment in two studies was conducted to investigate willingness to fly in autonomous air taxis among people from the United States and India. The first study used a 2 x 2 x 2 factorial analysis to test the effects of nationality, automatic airframe parachute availability, and remote pilot system availability on willingness to fly. People from India were more willing to fly than people from the United States, and people in general were more willing to fly in an aircraft equipped with an automatic airframe parachute. The second study replicated the effects of the first and tested whether two aspects of cultural orientation mediated the relationship between safety system availability and willingness to fly. Cultural orientation was not found to significantly mediate the relationship among people from the United States or India.
Categories: Graduate
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Assessing If Motivation Impacts General Aviation Pilots’ Persistence in Varying Weather Conditions
PI Sabrina Woods
CO-I Scott Winter
Continued flight under visual flight rules into instrument meteorological conditions is the predominant cause for fatal accidents by percentage, for general aviation aircraft operations. It is possible that a pilot’s motivation or reason for flying will override other safer, more logical courses of action when a hazard presents itself. The decision appears to stem from a willingness to persist in a course of action despite factors that indicate an alternate and safer course is warranted. This research addresses what is currently presumed about the decision to continue flying under visual flight rules into instrument conditions and marries those ideas with the extensive studies on how theoretically affects the decision-making process.
The research used a quantitative factorial experimental design and explored what bearing, if any, does type of motivation, or meteorological condition, or the interaction of the two have on a pilot’s willingness to persist in visual flight rule into instrument meteorological conditions. The researcher applied fundamental motivation theory and aviation regulation in the development of scenarios that were used to assess a pilot’s willingness to persist in unsafe weather conditions, and to determine what role motivation and the weather conditions might have played in that decision. A 3x3 factorial design was followed, and the method of analysis was a two-way mixed analysis of variance.
The independent variable meteorological condition indicated a significant effect on the dependent variable willingness to persist, and the independent variable motivation did not indicate a significant effect. The interaction between meteorological condition and motivation resulted in a significant effect on the dependent variable, particularly in the marginal weather condition, although with a low effect size. This result suggests that those who are motivated to fly for a specific reason or reasons might be more willing to persist over those who have no real reason to be flying. A recommendation for future research is that the experiment be replicated in a direct observation experimental design in either a full or partial motion simulator.
Further defining how motivation and meteorological conditions influence aeronautical decision-making can change the way aviation safety advocates, academics, regulators, and industry approach the issue. The results of this research could help determine what part of aeronautical decision making is objective and what is more subject to a person’s base desires.
Categories: Graduate
11-19 of 19 results