Stephen Rice

The Effect of Chart Type on Pilots’ Response Time

Electronic flight bags have become common place in commercial and general aviation flight decks. These tools provide for a compact and concise methods of carrying charts, procedure manuals, policies, and flight-related communications. On devices with connectivity, these tools can even be used to download real-time weather and file flight plans or even serve as a moving map by connecting a portable GPS receiver. However, with the proliferation of these devices, few studies have searched for any performance differences in pilots between these electronic charts and traditional paper charts. The purpose of this study was to compare pilots response time when answering a series of 30 questions related to instrument approach procedures using an electronic chart display, followed by paper charts. Twenty-seven instrument flight rated participants completed the repeated measures design using a desktop computer. The study simulated an event where the pilot’s electronic flight bag failed, and they had to use paper charts as a backup. The results of the study suggest a significant increase in participant response time when using paper charts compared to electronic ones. Participants response time using paper chart also did not significantly increase from their first trial using paper to their last trial using paper. Additional research should be completed to explore this relationship further and determine if the use of electronic charts are resulting in an unintended degradation of other pilot skills.

Driverless Ambulances: A Possibility, but Will Patients Ride?

Emergency Medical Services (EMS) provide a needed and necessary service in the healthcare industry worldwide. However, many EMS agencies find themselves understaffed to fill the needs of the communities they serve. As a result, this can lead to decreases in the quality of service provided in times of emergencies. Simultaneously, technology is advancing in driverless vehicles which pose the question of the possibility of building driverless ambulances and if so, patients’ willingness to ride in them. Therefore, the purpose of this study was to determine patients’ willingness to ride in an ambulance operated autonomously as opposed to one driven by a human. Affect measures were collected to determine if affect mediated the relationship between willingness to ride and the type of ambulance configuration. The research used a three-study approach to answer the research questions. First, a general scenario was used to examine patients willingness to ride in an ambulance based on a human or driverless condition. In Study 2, the affect was implemented to serve as a mediator between the type of operator, human or driverless. In Study 3, the researchers used the six universal facial expressions to determine if specific emotions could be identified as mediators between the condition and willingness to ride score. Through the three studies, the findings indicated that patients were less willing to ride in the scenario where the ambulance was operated autonomously than in the traditional configuration. A significant interaction was found between gender and type of ambulance configuration, where females were less willing to ride in the autonomous ambulance than males. Affect was found to act as a mediator between willingness to ride and the type of ambulance. Additionally, through the use of the six universal facial expressions, it was determined that the mediating emotions for males were fear and happiness, and the mediating emotion for females was anger. In general, participants were not willing to ride in driverless ambulances; however, this finding is also limited by the hypothetical scenario posed in this study which was the need to be transported to the hospital due to phoning 911 in an emergency. Additional research should investigate how patients would feel about riding in a driverless ambulance based on the type of condition as it is possible the willingness to ride may be different in a non-emergency scenario. There may also be other factors that could predict a patient’s willingness to ride in a driverless ambulance. In summary, while driverless technology is becoming a near-term possibility, further research is needed into whether patients would be willing to accept this technology for usage.

Which Factors Predict Consumer Willingness to Ride in Driverless Vehicles

Driverless vehicles are already in development and predicted to enter the market in a matter of years. Previous research centered on driverless vehicles has aimed to gauge whether or not consumers are willing to ride in different types of driverless vehicles. However, the current research investigated different variables that may influence consumer willingness to ride in a driverless vehicle. Variables investigated included demographic variables, emotions, and other information collected by researchers based on a theoretical framework. Participants responded to a willingness to ride scale, as well as different questionnaires and demographic surveys. Out of thirteen possible predictor variables, three were significant: happiness, fear, and value. In a regression model, these three variables accounted for 77% of the variance in the data. These findings contribute to the knowledge of consumer perceptions, as well as inform the current market. Implications for future research, as well as limitations, are also discussed.

Perceptions of Cockpit Configurations: A Culture and Gender Analysis

ABSTRACT Objective: With the advancement of technology in recent years the topic of autonomous, pilotless cockpits have emerged. The rhetoric of this article revolves around passenger perceptions and their willingness to fly on board such aircraft. Background: Although studies have been conducted to gauge similar consumer perceptions, this study compared 3 different 2-pilot configurations based on pilot gender to that of the autonomous or automated cockpit. These configurations included 2 male pilots, 1 male and 1 female pilot, and 2 female pilots. Method: 433 participants from India and the United States were recruited using Amazon’s Mechanical Turk and responded to questions designed to measure consumer perceptions on the topic at hand. The study used Rice, Mehta, et al.’s (2015) willingness-to-fly scale to collect the data. Results: The results suggested that all participants were more willing to fly on board all 3 types of 2-pilot configurations as opposed to the autonomous cockpit. However, Indian male participants showed a decrease in willingness to fly on board the 2-female-pilot configurations as opposed to the other 2-human-pilot configurations. Additionally, U.S. participants were much less willing to fly on board the autonomous configuration as compared to their Indian counterparts. Conclusion: The findings suggest that all participants were least willing to fly on aircraft flown completely by an autopilot. Differences were also noted based on pilot gender.

Recognizing the Role of Consistency in a Delayed Memory Task

Past research on short-term memory decay has found that participants are more efficient at remembering information when the delay between stimuli presentation and recall is short as opposed to long. In the current study we used Potential Performance Theory (PPT) to identify the role that both random and systematic factors play in observed memory performance over a delay. We presented participants with a string of letters followed by either a 2-second or 16-second delay. Following the delay, participants were presented with a two alternative forced choice (2AFC) display where they were asked to determine whether the matching string was in the first or second display. The findings indicate that inconsistency is primarily responsible for the decrements in observed performance that can be seen over a time delay. Theoretical and practical applications are discussed.

An Affect-Trust (A-T) Model With Regards to Technological Errors

Much research has differentiated between the effects of automation false alarms and misses on operator trust and subsequent behavior. Further research has demonstrated that trust is a multiple-process construct that mediates the relationship between automation errors and behavior. The purpose of the current study was to expand on this model by incorporating affect as a mediating variable between smoke detector errors and trust. This expanded model, which we refer to as the Affect-Trust model, is supported by two experiments. The experiments involved mediation analyses, which revealed that affect almost totally mediates the relationship between both types of smoke detector errors and trust.