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Inadequate situation awareness and response are increasingly recognized as prevalent critical errors that lead to young driver crashes. To identify and assess key indicators of young driver performance (including situation awareness), we previously developed and validated a Simulated Driving Assessment (SDA) in which drivers are safely and reproducibly exposed to a set of common and potentially serious crash scenarios. Many of the standardized safety measures can be calculated in near real-time from simulator variables. Assessment of situation awareness, however, largely relies on time-consuming data reduction and video coding. Therefore, the objective of this research was to develop a near real-time automated method for analyzing general direction and location of driver's gaze in order to assess situation awareness.

This IC engine improvement addresses ICE’s inherent efficiency limit through innovative mechanical design of a consolidated system encompassing intake bypass and coordinating injection mechanism. In principle, the exhaust energy is recuperated to modulate intake temperature, in the meantime, multi-staged injection control is proposed that enhances in-cylinder thermal efficiency. To be specific, a CFD-optimized bypass is constructed alongside the intake and injection design which utilizes multi-stage variable mixing precisely, taking full advantage of exhaust temperature elevation. Regenerative heat gained through exhaust system gives rise to flexible amount of thermal dynamics adjustment to the intake, which consequently delivers more robust combustion efficiency as well as lower emission metrics. A flow control valve is developed at intake interface enables modular variable intake routing supporting engine efficiency promotion.

Computational modeling is a potentially powerful tool to provide information about the mechanisms of traumatic brain injury. In order to ensure that the estimates calculated by these computer models provide the most useful information, it is essential that these models contain accurate central nervous system (CNS) tissue properties. Previous material property measurements lack strict control over crucial experimental parameters that may influence material properties and tail to examine any regional variation in the measured response. To address these issues, we measured the material response of two regions of the CNS, the brainstem and the cerebrum. Specifically, adult porcine tissue was subjected to high loading rate mechanical deformation using a custom designed oscillatory shear device. Complex shear moduli were calculated over a range of frequencies (20-200 Hz) at two engineering strain amplitudes (2.5%, and 5.0%).

A finite element model of cerebral contusion in the rat was developed and compared to experimental injury maps demonstrating blood-brain barrier (BBB) breakdown. The model was exercised at the nine unique loading conditions used experimentally. Logistic regressions of four variables, maximum principal logarithmic strain (LEP), maximum principal stress (SP), strain energy density (SEN), and von Mises stress (MIS) demonstrated highly significant confidence in the prediction of the 50th percentile values (chi-squared, p<0.00001). However, only values for LEP were invariant across loading conditions. These results suggest that the BBB is most sensitive to LEP, and that breakdown occurs above a strain of 0.188 +/- 0.0324.

Digital human modeling (DHM) progress worldwide will be much faster and cohesive if the diverse community now developing simulations has a global blueprint for DHM, and is able to work together efficiently. DHM developers and users can save time by building on each other's work. This paper highlights a panel discussion on DHM goals and strategic plans for the next decade to begin formulating the international blueprint. Four subjects are chosen as the starting points: (1) moving DHM into the public safety and internet arenas, (2) role of DHM in computer assisted surgery and automotive safety, (3) DHM in defense applications, and (4) DHM to improve workplace ergonomics.

Carnegie Mellon Driving Research Center, together with ISIM, is presently involved in the design and development of an Advanced Human Factors Research and Driving Training Research Facility. The facility has been designed to address human factors issues and driver training issues. Human factors interests include developing countermeasures for fatigue and driver/vehicle interface issues. Driver training issues include validating the usefulness of simulators for driver training, developing effective curricula and investigating simulator fidelity needed for effective training. A key component of the facility is the Carnegie Mellon TruckSim that will be capable of simulating a variety of commercial and emergency vehicles using interchangeable cabs mounted to a common motion platform. TruckSim's modular configuration will allow for rapid and cost effective design of experiments and training scenarios. A first research program to evaluate fatigue countermeasures is presented as an example.

Traumatic brain injury finite element analyses have evolved from crude geometric representations of the skull and brain system into sophisticated models which take into account distinct anatomical features. However, two distinct finite element modeling approaches have evolved to account for the relative motion that occurs between the skull and cerebral cortex during traumatic brain injury. The first and most common approach assumes that the relative motion can be estimated by representing the cerebrospinal fluid inside the subarachnoid space as a low shear modulus, virtually incompressible solid. The second approach assumes that the relative motion can be approximated by defining a frictional interface between the cerebral cortex and dura mater. This study presents data from an experimental model of traumatic brain injury coupled with finite element analyses to evaluate the modeling approach's ability to predict specific forms of traumatic brain injury.

To meet the increasing electrical power demands for advanced internal combustion engine (ICE) vehicles, auxiliary power units (APUs) are of growing interest. Fuel cell based APUs offer the potential for high chemical-to-electrical conversion efficiency with low noise and low emissions. It has recently been shown that solid oxide fuel cells (SOFCs) can be used to directly convert the chemical energy of liquid hydrocarbon fuels to electricity. Because the combustion reaction takes place by direct oxidation of vaporized fuel at the fuel cell anode, the expectation exists for development of compact, reformerless APUs that can operate on the same fuel that the ICE uses for vehicle propulsion. Critical issues for the transportation SOFC-APU applications are fast start-up and the need to survive extensive thermal cycling.

To be practical, auxiliary power units (APUs) should operate on the same fuels that the internal combustion engine (ICE) uses for vehicle propulsion. Solid oxide fuel cells (SOFCs) have previously been shown to be able to convert the chemical energy of certain room-temperature-liquid hydrocarbon fuels (toluene and synthetic diesel fuel) to electricity by direct oxidation. Because such SOFCs operate without reformers, the systems based on these SOFCs are expected to be compact. To work with existing infrastructure fuels, the cells must be able to tolerate typical contaminants such as sulfur that are found in the everyday fuels. In this paper, we report on recent laboratory results that show direct oxidation SOFCs with ceria-copper anodes can provide at least 2 hours operation in the presence of 200 ppm sulfur in the fuel. Also, a laboratory cell has been run for 12 hours on regular unleaded gasoline.

Finite element (FE) models are commonly used for automotive crashworthiness design. However, even with increasing speed of computers, the FE-based simulation is still too time-consuming when simulating the complex dynamic process such as vehicle crashworthiness. To improve the computational efficiency, the response surface model, as the surrogate of FE model, has been widely used for crashworthiness optimization design. Before introducing the surrogate model into the design optimization, the surrogate should satisfy the accuracy requirements. However, the bias of surrogate model is introduced inevitably. Meanwhile, it is also very difficult to decide how many samples are needed when building the high fidelity surrogate model for the system with strong nonlinearity. In order to solve the aforementioned problems, the application of a kind of surrogate optimization method called Efficient Global Optimization (EGO) is proposed to conduct the crashworthiness design optimization.

As vehicles with SAE level 2 of autonomy become more widely deployed, they still rely on the human driver to monitor the driving task and take control during emergencies. It is therefore necessary to examine the Human Factors affecting a driver’s ability to recognize and execute a steering or pedal action in response to a dangerous situation when the autonomous system abruptly requests human intervention. This research used a driving simulator to introduce the concept of level 2 autonomy to a cohort of 60 drivers (male: 48%, female: 52%) of different age groups (teens 16 to 19: 32%, adults: 35 to 54: 37%, seniors 65+: 32%). Participants were surveyed for their perspectives on self-driving vehicles. They were then assessed on a driving simulator that mimicked SAE level 2 of autonomy. Participants’ interaction with the HMI was studied.

Computational ergonomic analyses are often laboriously tested one task at a time. As digital human models improve, we can partially automate the entire analysis process of checking human factors requirements or regulations against a given design. We are extending our Parameterized Action Representation (PAR) to store requirements and its execution system to drive human models through required tasks. Databases of actions, objects, regulations, and digital humans are instantiated into PARs and executed by analyzers that simulate the actions on digital humans and monitor the actions to report successes and failures. These extensions will allow quantitative but localized design assessment relative to specific human factors requirements

Experimental tests using porcine brainstem samples were performed on a custom designed stress relaxation shear device. Tests were performed dynamically at strain rates >1 s−1, to three levels of peak strain (2.5%-7.5%). The directional dependence of the material properties was investigated by shearing both parallel and transverse to the predominant direction of the axonal fibers. Quasi-linear viscoelastic theory was used to describe the reduced relaxation response and the instantaneous elastic function. The time constants of the reduced relaxation function demonstrate no directional dependence; however, the relative magnitude of the exponential functions and the parameter representing the final limiting value are significantly different for each direction. The elastic function qualitatively demonstrates a dependence on direction. These results suggest that the brainstem is an anisotropic material.

The use of cerium oxide as an oxygen storage component in automotive three-way catalysis has been well established. More recently the need to thermally stabilize these materials against deactivation at higher temperatures has focused attention on doping of the ceria with a wide range of metal oxides. The role of these dopants in the stabilization mechanisms for ceria is not completely understood as they must perform the complex role of sintering inhibitor while promoting oxygen storage and release. The scattering of pulsed neutrons produced by a spallation source coupled with the Fourier analysis provides a powerful method to characterize the local atomic structure of complex systems such as mixed oxides. We demonstrate that by using this method it is possible to obtain valuable information on the local atomic structure of the CeO2/ZrO2 catalyst support that cannot be attained by the conventional diffraction methods.

Simulating human reach is still challenging when considering complex interactions with the environment. Standard approaches involve inverse kinematics (IK) methods and usually require a complete but exponential cost search in configuration space. In ergonomic applications, both “naturalness” and interactive performance are important. We describe a real-time, collision-free, sternum-rooted IK solution for an articulated human figure based on motion capture data, human strength models, and multi-joint coordination functions. Movement paths are discovered through spatial search in a partitioned workspace. The system generates natural collision-free reach motions in real-time. The resulting animations and statistics demonstrate the efficacy of this approach.

The earliest Digital Human Modeling systems were non-interactive analysis packages with crude graphics. Next generation systems added interactivity and articulated kinematic human models. The newest systems use real-time computer graphics, deformable figures, motion controllers, and user interfaces. Our long-term goal is to free the user as much as possible from interactive human model manipulation through direct understanding and execution of task instructions. We present a next generation DHM testbed that includes a scriptable interface, real-time collision-avoidance reach, empirical joint motion models, a versatile locomotion engine, motion capture and synthetic motion blends and combinations, and a smooth skinned scalable human model.

Frontal and temporal lobe contusions that were caused by a single sagittal plane angular acceleration impulse were analyzed. At neuropathological exam the depth, extent, and location of contusions were mapped and described according to a classification previously developed for human use. Of 30 rhesus monkeys subjected to a single angular acceleration impulse, 13 had no frontal or temporal contusion (Group 1), 8 had only frontal contusion (Group 2) and 9 had temporal contusions (Group 3). Correlation with angular acceleration, tangential acceleration and tangential force showed that the three groups were statistically different. The mean peak positive tangential force for Groups 1-3 was 541, 659 and 766 newtons respectively (p<0.10). This suggested that as mechanical imput increased, frontal contusions occur before temporal contusions and that the threshold for frontal contusion is less than that for temporal contusion.

The principle of maximum entropy is used to obtain the prior probability distribution functions for critical creep-strain and creep-rupture characteristics of engineering materials, operating at known high temperatures and uniaxial stresses. From the prior distribution function obtained, reliability function which is simply the probability of successful operation of the material, can be derived for specified critical creep-strain and creep-rupture modes of failure. An attempt is made to derive the reliability functions from prior considerations of the mechanics of failure, and the mechanical and physical characteristics of engineering materials. This work assumes that mechanical creep design reliability functions for creep-rupture and critical creep-strain modes of structural elements can have values such that the failure of the elements can occur either by any of the modes of failure or by the assumed combined modes of failure.

An attempt is made to show that a transportation system as such is too "open" for sound planning, and that the larger interaction system (including the users of transportation and their bases at home and work) must be considered. This requires a detailed understanding of micro-behavior, social goals, and public policy alternatives in a wide range of situations.

Autonomous vehicles (AVs) have already driven millions of miles on public roads, but even the simplest scenarios have not been certified for safety. Current methodologies for the verification of AV’s decision and control systems attempt to divorce the lower level, short-term trajectory planning and trajectory tracking functions from the behavioral rules-based framework that governs mid-term actions. Such analysis is typically predicated on the discretization of the state space and has several limitations. First, it requires that a conservative buffer be added around obstacles such that many feasible plans are classified as unsafe. Second, the discretized controllers modeled in this analysis require several refinement steps before being implementable on an actual AV, and typically do not allow the specification of comfort-related properties on the trajectories. Consumer-ready AVs use motion planning algorithms that generate smooth trajectories.