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No full textMonica is in a top that shows off her body. This top is cooler than her last as she begins to calm down as a character and settle into her new life.https://ir.uiowa.edu/costume_design/1109/thumbnail.jp
Spots Renderings
No full textAnother group of renderings to communicate my design ideas for characters like Monica, Luis and Eugenio. The renderings were a guide to executing the final look of the production. I am very happy with Eugenio’s cassock and how the costume looked on stage next to the rendering.https://ir.uiowa.edu/costume_design/1106/thumbnail.jp
Mind-Wandering and Driving: Comparing Thought Report and Individual Difference Measures
Get PDFMind-wandering is a cognitive state in which attention is diverted from the main task and towards more personal thoughts, which can interfere with performance. This study investigated differences in patterns of mind-wandering and driving performance measured during thought-probe versus post-task selfreport conditions, and further differentiated based on individual differences in working memory—as measured by the Operation Span (OSPAN) and Sustained Attention to Response Task (SART). Participants completed two 30-minute drives. Those in the thought-probe condition were asked whether they were thinking of driving; the proportion of trials where they answered “no” was used as the index of mind-wandering. In the post-task condition participants estimated the percentage of time they had mind-wandered during each drive. Speed, steering variability, headway distance, and hazard response time to a lead vehicle braking were also measured. Results showed that the magnitude of mind-wandering captured in the thought-probe condition was greater than in the post-task condition, though hazard response times were also faster despite greater mindwandering reports. Higher OSPAN scores were associated with greater reports of mind-wandering, but only in the post-task condition. Conversely, in the post-task condition those with low SART scores responded slower to hazards than those with high scores; in the thought-probe condition these groups did not differ. Findings indicate a differential impact of report-type on participant experience, emphasizing the need for more covert measures of mind-wandering—e.g., eyetracking or electroencephalography—that provide accurate estimates of task engagement but don’t interfere with task flow
Recognition of Manual Driving Distraction Through Deep-Learning and Wearable Sensing
Get PDFThe goal of this study is to design a novel framework incorporating deep-learning techniques and wearable sensors to recognize manual distractions during driving. Manual distraction is defined as hands off the wheel for any reason (e.g. trying to get a cell phone). In this preliminary study, participants were tasked to drive in city street and highway scenarios in a driving simulator. Verbal instructions prompted participants to perform various manual distraction tasks. The motion of driver’s right wrist during driving was recorded by a wearable inertial measurement unit. A deep-learning technique called convolutional neural network (CNN) was then constructed and trained based on 72% of the experiment trials, and evaluated by the remaining 28% of trials. The results indicated that the convolutional neural network is able to recognize the type of manual distraction task based on the right wrist motion with 87.0% accuracy and F1-score of 0.87. The results indicated that there is a good potential to apply deep-learning techniques and wearable sensing to monitor driver’s inattention status
A Survey Study Measuring People\u27s Preferences Towards Automated and Non-Automated Ridesplitting
Get PDFRidesplitting is both common and important as it facilitates daily transportation needs. Alongside an increase in ridesplitting is the introduction of automated driving systems, which together, bring out the possibility of automated ridesplitting. However, previous studies have identified resistance in the acceptance of automated driving systems. In light of past research on automated driving systems, we used a survey to compare people’s preferences of automated ridesplitting to non-automated ridesplitting. Statistical and text mining techniques were leveraged to analyze the results. We found similarities in the numeric responses of important factors concerning automated and non-automated ridesplitting whereas there were large differences between automated and nonautomated ridesplitting in the text responses. Additionally, people prioritized cost and time in both automated and non-automated ridesplitting. These results can be used in the design of future ridesplitting services, especially with respect to increasing acceptance of and trust in automated ridesplitting services
Is Driving Simulation a Viable Method for Examining Drivers\u27 Ethical Choices? An Exploratory Study
Get PDFAdvanced vehicle technologies promise improved road safety but may still be subjected to situations where choices have to be made regarding safety impact to other road users. There is debate about the principles that should guide the programming of choices into automation algorithms, and an acknowledgment that choices made by automation may be subject to more scrutiny than those by humans. To better understand the landscape of decisions that human drivers encounter, it is important to examine the rationale, calculus, and motivations behind such choices. While there are various methods to examine human decision making, doing so in an ecologically valid manner is challenging, especially in this context of driving. To that end, this study was conducted to examine if driving simulation could help understand drivers’ ethical choices. Participants drove a route in a driving simulator that was programmed to end in a crash situation, one that placed the driver in a position of choosing between two crash outcomes. Participants were asked, after the fact, about their perceptions of the simulation and their decisions. Results indicate that drivers generally accepted simulation as realistic, but their post-experiment choices did not align with their actual decisions during the drive. Findings may have implications for the experimental study of ethical behaviors
Spatially Biased Eye Movements in Older Drivers with Glaucoma and Visual Field Defects
Get PDFPatients with glaucoma are at greater driving safety risk due to visual field defects. These driving safety risks may be mitigated by compensatory eye movements. We measured spatial allocation of eye movements in a panoramic driving simulator in 8 drivers with glaucoma and 5 with suspected glaucoma. All completed a driving simulator visual field task under three separate conditions: (1) parked with a naturalistic background (Baseline condition); (2) driving on a rural highway (Driving condition); and (3) driving and completing a competing auditory attention task (PASAT condition). Results showed that: (1) drivers with larger binocular visual field defects showed more restricted, spatially biased eye movements, and (2) greater task load led to more spatially biased eye movements in drivers with larger binocular visual field defects. Findings provide preliminary evidence of eye movement patterns that may reflect compensatory behaviors in drivers with glaucomatous visual fields. Better understanding of the relationship between visual field deficits, eye movement patterns, and driving in glaucoma can help inform countermeasures to improve safety and mobility in drivers with visual impairments
Magnetoencephalography during Simulated Driving: A New Paradigm for Driver Assessment
Get PDFIncreasingly, vehicles are equipped with assistive devices and advanced warning systems to mitigate driver errors, which account for 94% of motor vehicle crashes. However, these technologies require humans to appropriately respond or take over the vehicle. If we want to design effective aids, we need to better understand the neural mechanisms underlying driver error and test how the brain responds to countermeasures. For this, we need sensitive measures of brain activity during driving. This paper present a new paradigm for driver assessment, using magnetoencephalographic (MEG) recording of whole cortex neural oscillatory activity while participants undergo an ecologicallyrelevant simulated driving experience of graded complexity. A pilot experiment set out to demonstrate that expected and motor cortex responses to basic drivingrelated movements (without salient cues) could be recorded, without significant artifact. Following this, a preliminary study of adults (n=5) explored if additional cognitive neural responses to increasing driving task demands can be identified. This paradigm was successfully piloted and preliminary results reveal localized brain regions of expected motor cortex activity, as well as power increases in the frontal lobe. This paradigm can be used to identify not only the neural mechanisms underlying driver errors, but also measure the impact of assistive and alert/warning technologies on these mechanisms in both typical and impaired populations of drivers
The Heterogeneity Principle
Get PDFThe theoretical foundation of the Naturalistic Driving (ND) MixedSafety-Critical Event (SCE) methodology is found in the historical writings of H.W. Heinrich, a 20th century industrial safety engineer. Heinrich espoused the theory that serious accidents, minor ones, and even no-injury operator errors all had identical or highly similar causal mechanisms and that accident consequences were essentially unlinked to causes. This became the basis for today’s ND MixedSCE method, whereby a variety of mostly non-crash avoidance maneuvers (e.g., hard braking, swerves) and other kinematic events (e.g., lane drifts) are aggregated by researchers to form a dependent variable dataset ostensibly representative of important and harmful crashes. This paper examines this approach and finds it to be invalidated by the pervasive causal heterogeneity of crashes and would-be surrogates. Crashes are heterogeneous horizontally by type and vertically by severity. This paper argues instead for the heterogeneity principle as the foundational assumption and guiding tenet for any effort to extrapolate causal evidence from surrogates (e.g., non-crashes or minor crashes) to a different and more important target crash population such as serious crashes
Speed Anticipation Characteristic with Optical Flow for Driver Behavior Assessment of Older Drivers
Get PDFThe objective of this study is to clarify the relationship between the speed anticipation characteristic with optical flow derived from self-motion and driver behavior of older drivers for future driver assessment. We focused on speed anticipation with optical flow because anticipated speed is assumed to influence behavior at unsignalized intersections with limited visibility, which is an accidentprone situation for the older drivers in Japan. To assess the characteristic, we constructed a novel test by revising a similar test. We conducted an experiment with older drivers that consisted of the novel test and an on-road driving test. The experiment results showed that the speed anticipation characteristic with optical flow had a significant effect on older drivers’ behavior at intersections and drivers who anticipated speed faster drove slower and safer