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Recent Submissions

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    Trust in Autonomous Vehicles: The case of Tesla Autopilot and Summon
    (2017-10-05) Dikmen, Murat Burns, Catherine
    Autonomous driving is on the horizon. Vehicles with partially automated driving capabilities are already in the market. Before the widespread adoption however, human factors issues in the automated driving context need to be addressed. One of the key components of this is how much drivers trust in automated driving systems and how they calibrate their trust and reliance based on their experience. In this paper, we report the results of a survey conducted with Tesla drivers about their experiences with two advanced driver assistance systems, Autopilot and Summon. We found that drivers have high levels of trust in Autopilot and Summon. Trust decreased with age for Autopilot but not for Summon. Drivers who experienced unexpected behaviors from their vehicles reported lower levels of trust in Autopilot. Over time, trust in these systems increased regardless of experience. Additionally, trust was correlated with several attitudinal and behavioral factors such as frequency of use, self-rated knowledge about these systems, and ease of learning. These findings highlight the importance of trust in real world use of autonomous cars. Also, the results suggest that previous
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    Predictability of decaying stratified turbulence
    (AIP Publishing, 2024-06-14) Diaz, Martín F.; Waite, Michael L.
    Predictability of geophysical fluid dynamics at various scales remains a crucial challenge for accurate weather and climate forecasting. Following the pioneering framework established by Lorenz, numerous studies on homogeneous and isotropic turbulence have demonstrated that flows characterized by diverse scales may exhibit limited predictability. This limitation arises from the inevitable amplification of errors in the initial conditions from small scales to larger scales, even if the initial error is confined to small scales. This research investigates the predictability of freely decaying homogeneous stratified turbulence, which serves as a representative model for small-scale geophysical turbulence where rotational effects are negligible. Direct numerical simulations are employed to assess predictability by analyzing the growth of errors introduced in pairs of simulations with near-identical initial conditions; errors are modeled as the difference field of the pair. Previous studies have established a connection between the finite range of predictability and the slope of the kinetic energy spectrum. In the context of stratified turbulence, the shape of the energy spectrum exhibits a dependence on the buoyancy Reynolds number (Reb), particularly at lower values of Reb. This work conducts a comparative analysis of both the energy spectra and the error growth behavior across different regimes of stratified turbulence, encompassing a range of Reb values from O(1) to O(10)⁠. The sensitivity of the obtained results to the introduced error is investigated. Modifying the geometrical shape of the error (spherical vs cylindrical complement) and the cutoff wavenumber while maintaining the initial error kinetic energy did not significantly alter the error dynamics. The results are robust to variations in the method of error introduction.
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    Wearable-sensor-based classification models of faller status in older adults
    (Public Library of Science, 2016-04-07) Howcroft, Jennifer; Lemaire, Edward D.; Kofman, Jonathan
    Wearable sensors have potential for quantitative, gait-based, point-of-care fall risk assessment that can be easily and quickly implemented in clinical-care and older-adult living environments. This investigation generated models for wearable-sensor based fall-risk classification in older adults and identified the optimal sensor type, location, combination, and modelling method; for walking with and without a cognitive load task. A convenience sample of 100 older individuals (75.5 ± 6.7 years; 76 non-fallers, 24 fallers based on 6 month retrospective fall occurrence) walked 7.62 m under single-task and dual-task conditions while wearing pressure-sensing insoles and tri-axial accelerometers at the head, pelvis, and left and right shanks. Participants also completed the Activities-specific Balance Confidence scale, Community Health Activities Model Program for Seniors questionnaire, six minute walk test, and ranked their fear of falling. Fall risk classification models were assessed for all sensor combinations and three model types: multi-layer perceptron neural network, naïve Bayesian, and support vector machine. The best performing model was a multi-layer perceptron neural network with input parameters from pressure-sensing insoles and head, pelvis, and left shank accelerometers (accuracy = 84%, F1 score = 0.600, MCC score = 0.521). Head sensor-based models had the best performance of the single-sensor models for single-task gait assessment. Single-task gait assessment models outperformed models based on dual-task walking or clinical assessment data. Support vector machines and neural networks were the best modelling technique for fall risk classification. Fall risk classification models developed for point-of-care environments should be developed using support vector machines and neural networks, with a multi-sensor single-task gait assessment.
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    Attentional effects on phenomenological appearance: How they change with task instructions and measurement methods
    (Public Library of Science, 2016-03-29) Anderson, Britt
    It has been reported that exogenous cues accentuate contrast appearance. The empirical finding is controversial because non-veridical perception challenges the idea that attention prioritizes processing resources to make perception better, and because philosophers have used the finding to challenge representational accounts of mental experience. The present experiments confirm that when evaluated with comparison paradigms exogenous cues increase the apparent contrast. In addition, contrast appearance was also changed by simply changing the purpose of the secondary task. When comparison and discrimination reports were combined in a single experiment there was a behavioral disassociation: contrast enhanced for comparison responses, but did not change for discrimination judgments, even when participants made both types of judgement for a single stimulus. That a single object can have multiple simultaneous appearances leads inescapably to the conclusion that our unitary mental experience is illusory.
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    Atheists and agnostics are more reflective than religious believers: Four empirical studies and a meta-analysis
    (Public Library of Science, 2016-04-07) Pennycook, Gordon; Ross, Robert M.; Koehler, Derek J.; Fugelsang, Jonathan A.
    Individual differences in the mere willingness to think analytically has been shown to predict religious disbelief. Recently, however, it has been argued that analytic thinkers are not actually less religious; rather, the putative association may be a result of religiosity typically being measured after analytic thinking (an order effect). In light of this possibility, we report four studies in which a negative correlation between religious belief and performance on analytic thinking measures is found when religious belief is measured in a separate session. We also performed a meta-analysis on all previously published studies on the topic along with our four new studies (N = 15,078, k = 31), focusing specifically on the association between performance on the Cognitive Reflection Test (the most widely used individual difference measure of analytic thinking) and religious belief. This meta-analysis revealed an overall negative correlation (r) of -.18, 95% Cl [-.21, -.16]. Although this correlation is modest, self-identified atheists (N = 133) scored 18.7% higher than religiously affiliated individuals (N = 597) on a composite measure of analytic thinking administered across our four new studies (d = .72). Our results indicate that the association between analytic thinking and religious disbelief is not caused by a simple order effect. There is good evidence that atheists and agnostics are more reflective than religious believers.