Matching Items (8)
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- All Subjects: Behavioral Sciences
- Genre: Academic theses
- Genre: Doctoral Dissertation
- Creators: Cooke, Nancy J.
- Status: Published
Description
Research on priming has shown that exposure to the concept of fast food can have an effect on human behavior by inducing haste and impatience (Zhong & E. DeVoe, 2010). This research suggests that thinking about fast food makes individuals impatient and strengthens their desire to complete tasks such as reading and decision making as quickly and efficiently as possible. Two experiments were conducted in which the effects of fast food priming were examined using a driving simulator. The experiments examined whether fast food primes can induce impatient driving. In experiment 1, 30 adult drivers drove a course in a driving simulator after being exposed to images by rating aesthetics of four different logos. Experiment 1 did not yield faster driving speeds nor an impatient and faster break at the yellow light in the fast food logo prime condition. In experiment 2, 30 adult drivers drove the same course from experiment 1. Participants did not rate logos on their aesthetics prior to the drive, instead billboards were included in the simulation that had either fast food or diner logos. Experiment 2 did not yielded faster driving speeds, however there was a significant effect of faster breaking and a higher number of participants running the yellow light.
ContributorsTaggart, Mistey. L (Author) / Branaghan, Russell (Thesis advisor) / Cooke, Nancy J. (Committee member) / Song, Hyunjin (Committee member) / Arizona State University (Publisher)
Created2014
Description
When discussing human factors and performance, researchers recognize stress as a factor, but overlook mood as contributing factor. To explore the relationship between mood, stress and cognitive performance, a field study was conducted involving fire fighters engaged in a fire response simulation. Firefighter participants completed a stress questionnaire, an emotional state questionnaire, and a cognitive task. Stress and cognitive task performance scores were examined before and after the firefighting simulation for individual cognitive performance depreciation caused by stress or mood. They study revealed that existing stress was a reliable predictor of the pre-simulation cognitive task score, that, as mood becomes more positive, perceived stress scores decrease, and that negative mood and pre-simulation stress are also positively and significantly correlated.
ContributorsGomez-Herbert, Maria Elena (Author) / Cooke, Nancy J. (Thesis advisor) / Becker, Vaughn (Committee member) / Branaghan, Russell (Committee member) / Hyunjin, Song (Committee member) / Arizona State University (Publisher)
Created2014
Description
Driving a vehicle is a complex task that typically requires several physical interactions and mental tasks. Inattentive driving takes a driver’s attention away from the primary task of driving, which can endanger the safety of driver, passenger(s), as well as pedestrians. According to several traffic safety administration organizations, distracted and inattentive driving are the primary causes of vehicle crashes or near crashes. In this research, a novel approach to detect and mitigate various levels of driving distractions is proposed. This novel approach consists of two main phases: i.) Proposing a system to detect various levels of driver distractions (low, medium, and high) using a machine learning techniques. ii.) Mitigating the effects of driver distractions through the integration of the distracted driving detection algorithm and the existing vehicle safety systems. In phase- 1, vehicle data were collected from an advanced driving simulator and a visual based sensor (webcam) for face monitoring. In addition, data were processed using a machine learning algorithm and a head pose analysis package in MATLAB. Then the model was trained and validated to detect different human operator distraction levels. In phase 2, the detected level of distraction, time to collision (TTC), lane position (LP), and steering entropy (SE) were used as an input to feed the vehicle safety controller that provides an appropriate action to maintain and/or mitigate vehicle safety status. The integrated detection algorithm and vehicle safety controller were then prototyped using MATLAB/SIMULINK for validation. A complete vehicle power train model including the driver’s interaction was replicated, and the outcome from the detection algorithm was fed into the vehicle safety controller. The results show that the vehicle safety system controller reacted and mitigated the vehicle safety status-in closed loop real-time fashion. The simulation results show that the proposed approach is efficient, accurate, and adaptable to dynamic changes resulting from the driver, as well as the vehicle system. This novel approach was applied in order to mitigate the impact of visual and cognitive distractions on the driver performance.
ContributorsAlomari, Jamil (Author) / Mayyas, AbdRaouf (Thesis advisor) / Cooke, Nancy J. (Committee member) / Gray, Robert (Committee member) / Arizona State University (Publisher)
Created2017
Description
While various collision warning studies in driving have been conducted, only a handful of studies have investigated the effectiveness of warnings with a distracted driver. Across four experiments, the present study aimed to understand the apparent gap in the literature of distracted drivers and warning effectiveness, specifically by studying various warnings presented to drivers while they were operating a smart phone. Experiment One attempted to understand which smart phone tasks, (text vs image) or (self-paced vs other-paced) are the most distracting to a driver. Experiment Two compared the effectiveness of different smartphone based applications (app’s) for mitigating driver distraction. Experiment Three investigated the effects of informative auditory and tactile warnings which were designed to convey directional information to a distracted driver (moving towards or away). Lastly, Experiment Four extended the research into the area of autonomous driving by investigating the effectiveness of different auditory take-over request signals. Novel to both Experiment Three and Four was that the warnings were delivered from the source of the distraction (i.e., by either the sound triggered at the smart phone location or through a vibration given on the wrist of the hand holding the smart phone). This warning placement was an attempt to break the driver’s attentional focus on their smart phone and understand how to best re-orient the driver in order to improve the driver’s situational awareness (SA). The overall goal was to explore these novel methods of improved SA so drivers may more quickly and appropriately respond to a critical event.
ContributorsMcNabb, Jaimie Christine (Author) / Gray, Dr. Rob (Thesis advisor) / Branaghan, Dr. Russell (Committee member) / Becker, Dr. Vaughn (Committee member) / Arizona State University (Publisher)
Created2017
Description
What makes a human, artificial intelligence, and robot team (HART) succeed despite unforeseen challenges in a complex sociotechnical world? Are there personalities that are better suited for HARTs facing the unexpected? Only recently has resilience been considered specifically at the team level, and few studies have addressed team resilience for HARTs. Team resilience here is defined as the ability of a team to reorganize team processes to rebound or morph to overcome an unforeseen challenge. A distinction from the individual, group, or organizational aspects of resilience for teams is how team resilience trades off with team interdependent capacity. The following study collected data from 28 teams comprised of two human participants (recruited from a university populace) and a synthetic teammate (played by an experienced experimenter). Each team completed a series of six reconnaissance missions presented to them in a Minecraft world. The research aim was to identify how to better integrate synthetic teammates for high-risk, high-stress dynamic operations to boost HART performance and HART resilience. All team communications were orally over Zoom. The primary manipulation was the communication given by the synthetic teammate (between-subjects, Task or Task+): Task only communicated the essentials, and Task+ offered clear and concise communications of its own capabilities and limitations. Performance and resilience were measured using a primary mission task score (based upon how many tasks teams completed), time-based measures (such as how long it took to recognize a problem or reorder team processes), and a subjective team resilience score (calculated from participant responses to a survey prompt). The research findings suggest the clear and concise reminders from Task+ enhanced HART performance and HART resilience during high-stress missions in which the teams were challenged by novel events. An exploratory study regarding what personalities may correlate with these improved performance metrics indicated that the Big Five trait taxonomies of extraversion and conscientiousness were positively correlated, whereas neuroticism was negatively correlated with higher HART performance and HART resilience. Future integration of synthetic teammates must consider the types of communications that will be offered to maximize HART performance and HART resilience.
ContributorsGraham, Hudson D. (Author) / Cooke, Nancy J. (Thesis advisor) / Gray, Robert (Committee member) / Holder, Eric (Committee member) / Arizona State University (Publisher)
Created2023
Description
As deception in cyberspace becomes more dynamic, research in this area should also take a dynamic approach to battling deception and false information. Research has previously shown that people are no better than chance at detecting deception. Deceptive information in cyberspace, specifically on social media, is not exempt from this pitfall. Current practices in social media rely on the users to detect false information and use appropriate discretion when deciding to share information online. This is ineffective and will predicatively end with users being unable to discern true from false information at all, as deceptive information becomes more difficult to distinguish from true information. To proactively combat inaccurate and deceptive information on social media, research must be conducted to understand not only the interaction effects of false content and user characteristics, but user behavior that stems from this interaction as well. This study investigated the effects of confirmation bias and susceptibility to deception on an individual’s choice to share information, specifically to understand how these factors relate to the sharing of false controversial information.
ContributorsChinzi, Ashley (Author) / Cooke, Nancy J. (Thesis advisor) / Chiou, Erin (Committee member) / Becker, David V (Committee member) / Arizona State University (Publisher)
Created2019
Description
Vehicular automation and autonomy are emerging fields that are growing at an
exponential rate, expected to alter the very foundations of our transportation system within the next 10-25 years. A crucial interaction has been born out this new technology: Human and automated drivers operating within the same environment. Despite the well- known dangers of automobiles and driving, autonomous vehicles and their consequences on driving environments are not well understood by the population who will soon be interacting with them every day. Will an improvement in the understanding of autonomous vehicles have an effect on how humans behave when driving around them? And furthermore, will this improvement in the understanding of autonomous vehicles lead to higher levels of trust in them? This study addressed these questions by conducting a survey to measure participant’s driving behavior and trust when in the presence of autonomous vehicles. Participants were given several pre-tests to measure existing knowledge and trust of autonomous vehicles, as well as to see their driving behavior when in close proximity to autonomous vehicles. Then participants were presented with an educational intervention, detailing how autonomous vehicles work, including their decision processes. After examining the intervention, participants were asked to repeat post-tests identical to the ones administered before the intervention. Though a significant difference in self-reported driving behavior was measure between the pre-test and post- test, there was no significant relation found between improvement in scores on the education intervention knowledge check and driving behavior. There was also no significant relation found between improvement in scores on the education intervention knowledge check and the change in trust scores. These findings can be used to inform autonomous vehicle and infrastructure design as well as future studies of the effects of autonomous vehicles on human drivers in experimental settings.
exponential rate, expected to alter the very foundations of our transportation system within the next 10-25 years. A crucial interaction has been born out this new technology: Human and automated drivers operating within the same environment. Despite the well- known dangers of automobiles and driving, autonomous vehicles and their consequences on driving environments are not well understood by the population who will soon be interacting with them every day. Will an improvement in the understanding of autonomous vehicles have an effect on how humans behave when driving around them? And furthermore, will this improvement in the understanding of autonomous vehicles lead to higher levels of trust in them? This study addressed these questions by conducting a survey to measure participant’s driving behavior and trust when in the presence of autonomous vehicles. Participants were given several pre-tests to measure existing knowledge and trust of autonomous vehicles, as well as to see their driving behavior when in close proximity to autonomous vehicles. Then participants were presented with an educational intervention, detailing how autonomous vehicles work, including their decision processes. After examining the intervention, participants were asked to repeat post-tests identical to the ones administered before the intervention. Though a significant difference in self-reported driving behavior was measure between the pre-test and post- test, there was no significant relation found between improvement in scores on the education intervention knowledge check and driving behavior. There was also no significant relation found between improvement in scores on the education intervention knowledge check and the change in trust scores. These findings can be used to inform autonomous vehicle and infrastructure design as well as future studies of the effects of autonomous vehicles on human drivers in experimental settings.
ContributorsReagan, Taylor (Author) / Cooke, Nancy J. (Thesis advisor) / Chiou, Erin (Committee member) / Gray, Robert (Committee member) / Arizona State University (Publisher)
Created2019
Description
The current study aims to explore factors affecting trust in human-drone collaboration. A current gap exists in research surrounding civilian drone use and the role of trust in human-drone interaction and collaboration. Specifically, existing research lacks an explanation of the relationship between drone pilot experience, trust, and trust-related behaviors as well as other factors. Using two dimensions of trust in human-automation team—purpose and performance—the effects of experience on drone design and trust is studied to explore factors that may contribute to such a model. An online survey was conducted to examine civilian drone operators’ experience, familiarity, expertise, and trust in commercially available drones. It was predicted that factors of prior experience (familiarity, self-reported expertise) would have a significant effect on trust in drones. The choice to use or exclude the drone propellers in a search-and-identify scenario, paired with the pilots’ experience with drones, would further confirm the relevance of the trust dimensions of purpose versus performance in the human-drone relationship. If the pilot has a positive sense of purpose and benevolence with the drone, the pilot trusts the drone has a positive intent towards them and the task. If the pilot has trust in the performance of the drone, they ascertain that the drone has the skill to do the task. The researcher found no significant differences between mean trust scores across levels of familiarity, but did find some interaction between self-report expertise, familiarity, and trust. Future research should further explore more concrete measures of situational participant factors such as self-confidence and expertise to understand their role in civilian pilots’ trust in their drone.
ContributorsNiichel, Madeline Kathleen (Author) / Chiou, Erin (Thesis advisor) / Cooke, Nancy J. (Committee member) / Craig, Scotty (Committee member) / Arizona State University (Publisher)
Created2019