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Currently, autonomous vehicles are being evaluated by how well they interact with humans without evaluating how well humans interact with them. Since people are not going to unanimously switch over to using autonomous vehicles, attention must be given to how well these new vehicles signal intent to human drivers from the driver’s point of view. Ineffective communication will lead to unnecessary discomfort among drivers caused by an underlying uncertainty about what an autonomous vehicle is or isn’t about to do. Recent studies suggest that humans tend to fixate on areas of higher uncertainty so scenarios that have a higher number of vehicle fixations can be reasoned to be more uncertain. We provide a framework for measuring human uncertainty and use the framework to measure the effect of empathetic vs non-empathetic agents. We used a simulated driving environment to create recorded scenarios and manipulate the autonomous vehicle to include either an empathetic or non-empathetic agent. The driving interaction is composed of two vehicles approaching an uncontrolled intersection. These scenarios were played to twelve participants while their gaze was recorded to track what the participants were fixating on. The overall intent was to provide an analytical framework as a tool for evaluating autonomous driving features; and in this case, we choose to evaluate how effective it was for vehicles to have empathetic behaviors included in the autonomous vehicle decision making. A t-test analysis of the gaze indicated that empathy did not in fact reduce uncertainty although additional testing of this hypothesis will be needed due to the small sample size.
Steady-state heat transfer by conduction forms the basis for understanding other steady-state and unsteady-state heat transfer in a rotary drum – conduction, convection and radiation. Statistical analysis is carried out to determine the effects of these process parameters and find optimal operating conditions, which will thereby improve the heat transfer efficiency in rotary drums. A stainless-steel drum with a diameter of 6 inches and a length of 3 inches was modeled in EDEM with silica beads of sizes 2 mm, 3 mm and 4 mm at fill levels of 10%, 17.5% and 25%, and at rotation rates of 2 rpm, 5 rpm and 10 rpm. It was found that the heating uniformity increased with decreasing particle size, decreasing fill level and increasing rotation rate. This research is the first step towards studying the other heat transfer modes and various other process parameters. Better understanding of the various heat transfer modes, when used in combination for heating the particles, will be beneficial in improving the operating efficiency, reducing material costs and leading to significant energy conservation on a global scale.