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The goal of this interview analysis was to explore and document the perceptions of two unique lane centering systems (S90’s Pilot Assist and CT6’s Super Cruise). Both systems offer a similar type of functionality (adaptive cruise control and lane centering), but have significantly different design philosophies and HMI (Human-Machine Interface) implementations. Twenty-four drivers drove one of the two vehicle models for a month as part of a field operational test (FOT) study. Upon vehicle return, drivers took part in a 60-minute semi-structured interview covering their perceptions of the vehicle’s various advanced driver-assistance systems (ADAS). Transcripts of the interviews were coded by two researchers, who tagged each statement with relevant system and perception code labels. For analysis, the perception codes were grouped into larger thematic bins of safety, comfort, driver attention, and system performance.

Rare earths are a group of elements whose availability has been of concern due to monopolistic supply conditions and environmentally unsustainable mining practices. To evaluate the risks of rare earths availability to automakers, a first step is to determine raw material content and value in vehicles. This task is challenging because rare earth elements are used in small quantities, in a large number of components, and by suppliers far upstream in the supply chain. For this work, data on rare earth content reported by vehicle parts suppliers was assessed to estimate the rare earth usage of a typical conventional gasoline engine midsize sedan and a full hybrid sedan. Parts were selected from a large set of reported parts to build a hypothetical typical mid-size sedan. Estimates of rare earth content for vehicles with alternative powertrain and battery technologies were made based on the available parts' data.

A set of devices for measurement of human balance orientation and eye movements in weightlessness was developed for neurovestibular experiments on Spacelab. The experiments involve astronaut motion, limb position changes, and moving visual fields, measurements are made of eye movements, muscular activity and orientation perception. This joint US/Canadian research program represent a group of closely related experiments designed to investigate space motion sickness, any associated changes in otolith-mediated responses occurring during weightlessness, and the continuation of changes to postflight conditions. The otoliths are a component of the vestibular apparatus which is located in the middle ear. It is responsible for maintaining the body's balance. Gravitational pull on the otoliths causes them to constantly appraise the nervous system of the position of the head with respect to the direction of gravity.

The fuel energy consumption of subsonic air transportation is examined. The focus is on identification and quantification of fundamental engineering design tradeoffs which drive the design of subsonic tube and wing transport aircraft. The sensitivities of energy efficiency to recent and forecast technology developments are also examined.

The aim of this study was to explore if fingernail delamination injury following EMU glove use may be caused by compression-induced blood flow occlusion in the finger. During compression tests, finger blood flow decreased more than 60%, however this occurred more rapidly for finger pad compression (4 N) than for fingertips (10 N). A pressure bulb compression test resulted in 50% and 45% decreased blood flow at 100 mmHg and 200 mmHg, respectively. These results indicate that the finger pad pressure required to articulate stiff gloves is more likely to contribute to injury than the fingertip pressure associated with tight fitting gloves.

Battery packs for Hybrids, Plug-in Hybrids, and Electric Vehicles are assembled from a system of modules (sheets) with a tight sheet metal casing around them. Each module consists of an array of individual cells which vary in the composition of electrodes and separator from one manufacturer to another. In this paper a general procedure is outlined on the development of a constitutive and computational model of a cylindrical cell. Particular emphasis is placed on correct prediction of initiation and propagation of a tearing fracture of the steel can. The computational model correctly predicts rupture of the steel can which could release aggressive chemicals, fumes, or spread the ignited fire to the neighboring cells. The initiation site of skin fracture depends on many factors such as the ductility of the casing material, constitutive behavior of the system of electrodes, and type of loading.

Determining the fundamental role of gravity in vital biological systems in space is one of six science and research areas that provides the philosophical underpinning for why NASA exists. The study of cells, tissues, and microorganisms in a spaceflight environment holds the promise of answering multiple intriguing questions about how gravity affects living systems. To enable these studies, specimens must be maintained in an environment similar to that used in a laboratory. Cell culture studies under normal laboratory conditions involve maintaining a highly specialized environment with the necessary temperature, humidity control, nutrient, and gas exchange conditions. These same cell life support conditions must be provided by the International Space Station (ISS) Cell Culture Unit (CCU) in the unique environment of space. The CCU is a perfusion-based system that must function in microgravity, at unit gravity (1g) on earth, and from 0.1g up to 2g aboard the ISS centrifuge rotor.

This paper presents the results of a study of how people interacted with a production voice-command based interface while driving on public roadways. Tasks included phone contact calling, full address destination entry, and point-of-interest (POI) selection. Baseline driving and driving while engaging in multiple-levels of an auditory-vocal cognitive reference task and manual radio tuning were used as comparison points. Measures included self-reported workload, task performance, physiological arousal, glance behavior, and vehicle control for an analysis sample of 48 participants (gender balanced across ages 21-68). Task analysis and glance measures confirm earlier findings that voice-command interfaces do not always allow the driver to keep their hands on the wheel and eyes on the road, as some assume.

The challenge of developing a robust, real-time driver gaze classification system is that it has to handle difficult edge cases that arise in real-world driving conditions: extreme lighting variations, eyeglass reflections, sunglasses and other occlusions. We propose a single-camera end-toend framework for classifying driver gaze into a discrete set of regions. This framework includes data collection, semi-automated annotation, offline classifier training, and an online real-time image processing pipeline that classifies the gaze region of the driver. We evaluate an implementation of each component on various subsets of a large onroad dataset. The key insight of our work is that robust driver gaze classification in real-world conditions is best approached by leveraging the power of supervised learning to generalize over the edge cases present in large annotated on-road datasets.

Advanced driver assistance systems (ADAS) are an increasingly common feature of modern vehicles. The influence of such systems on driver behavior, particularly in regards to the effects of intermittent warning systems, is sparsely studied to date. This paper examines dynamic changes in physiological and operational behavior during lane departure warnings (LDW) in two commercial automotive systems utilizing on-road data. Alerts from the systems, one using auditory and the other haptic LDWs, were monitored during highway driving conditions. LDW events were monitored during periods of single-task driving and dual-task driving. Dual-task periods consisted of the driver interacting with the vehicle’s factory infotainment system or a smartphone to perform secondary visual-manual (e.g., radio tuning, contact dialing, etc.) or auditory-vocal (e.g. destination address entry, contact dialing, etc.) tasks.

This paper evaluates the lag time in a turbocharged single cylinder engine in order to determine its viability in transient applications. The overall goal of this research is to increase the power output, reduce the fuel economy, and improve emissions of single cylinder engines through turbocharging. Due to the timing mismatch between the exhaust stroke, when the turbocharger is powered, and the intake stroke, when the engine intakes air, turbocharging is not conventionally used in commercial single cylinder engines. Our previous work has shown that it is possible to turbocharge a four stroke, single cylinder, internal combustion engine using an air capacitor, a large volume intake manifold in between the turbocharger compressor and engine intake. The air capacitor stores compressed air from the turbocharger during the exhaust stroke and delivers it during the intake stroke.

The combustion process after auto-ignition is investigated. Depending on the non-uniformity of the end gas, auto-ignition could initiate a flame, produce pressure waves that excite the engine structure (acoustic knock), or result in detonation (normal or developing). For the “acoustic knock” mode, a knock intensity (KI) is defined as the pressure oscillation amplitude. The KI values over different cycles under a fixed operating condition are observed to have a log-normal distribution. When the operating condition is changed (over different values of λ, EGR, and spark timing), the mean (μ) of log (KI/GIMEP) decreases linearly with the correlation-based ignition delay calculated using the knock-point end gas condition of the mean cycle. The standard deviation σ of log(KI/GIMEP) is approximately a constant, at 0.63. The values of μ and σ thus allow a statistical description of knock from the deterministic calculation of the ignition delay using the mean cycle properties

In today's business climate rapid access to, and implementation of, new technology is essential to enhance competitive advantage. In the past, universities have been used for research contracts, but to fully utilize the intellectual resources of education institutions, it is essential to approach these relationships from a new basis: alliance. Alliances permit both parties to become active participants and achieve mutually beneficial goals. This paper will examine the drivers and challenges for industrial -- university alliances from both the industrial and academic perspectives.

The National Space Biomedical Research Institute (NSBRI), established in 1997, is a twelve-university consortium dedicated to research that will impact mankind's next exploratory steps. The NSBRI's Education and Public Outreach Program (EPOP), is supporting NASA's education mission to, “Inspire the next generations…as only NASA can,” through a comprehensive Kindergarten through post-doctoral education program. The goals of the EPOP are to: communicate space exploration biology to schools; support undergraduate and graduate space-based courses and degrees; fund postdoctoral fellows to pursue space life sciences research; and engage national and international audiences to promote understanding of how space exploration benefits people on Earth. NSBRI EPOP presents its accomplishments as an educational strategy for supporting science education reform, workforce development, and public outreach.

Cranking and startup fuel control has become increasingly important due to ever tightening emission requirements. Additionally, engine-off strategies during idle will require substantially more engine startup events with the associated need for very clean starts. Thus, knowledge of an engine's Air-Fuel Ratio (AFR) during its early cycles is necessary in order to optimize cranking and startup fueling. This paper examines and compares two methods of measuring an engine's AFR during engine startup (approximately the first second of operation); an in-cylinder technique using a Fast Flame Ionization Detector (FFID) and the conventional exhaust based Universal Exhaust Gas Oxygen (UEGO) sensor method. Engine starts using a Ford Zetec engine were performed at three different temperatures (0, 20 and 90 C) as well as different initial engine starting positions.

Human explorers of planetary surfaces would benefit greatly from a spacesuit design that facilitates locomotion. To aid in the development of such an extravehicular activity suit, a design effort incorporating the concept of mechanical counter pressure (MCP) was undertaken. Three-dimensional laser scanning of the human body was used to identify the main effects of knee flexion angle on the size and shape of the leg. This laser scanning quantified the changes in shape that must be supported by an MCP garment and the tension that must be developed to produce even MCP. Evaluation of a hybrid-MCP concept using inextensible materials demonstrated strong agreement between experimental data and a mathematical model with rigid cylinder geometry. Testing of a form-fitting garment on the right lower leg of a subject demonstrated successful pressure production. Further research is required to evaluate how evenly pressure can be distributed using the hybrid-MCP concept.

Extravehicular activity (EVA) is investigated through experiments testing an actual extravehicular mobility unit (EMU) performing several EVA tasks in the laboratory, and a dynamic model of the EMU space suit is developed. Building directly on earlier work in EVA simulation, the space suit model was created from mass, inertia, and performance data to augment the unsuited 12-segment human model used in previous studies. A modified Preisach model was used to mathematically describe the hysteretic torque characteristics of joints in a pressurized space suit, and implemented numerically based on observed suit parameters. Computational simulations, based loosely on a 1995 EVA involving manipulation of the Spartan astrophysics payload, were performed to observe the effect of suit constraints on simulated astronaut performance.

A method for detecting drivers' intentions is essential to facilitate operating mode transitions between driver and driver assistance systems. We propose a driver behavior recognition method using Hidden Markov Models (HMMs) to characterize and detect driving maneuvers and place it in the framework of a cognitive model of human behavior. HMM-based steering behavior models for emergency and normal lane changes as well as for lane keeping were developed using a moving base driving simulator. Analysis of these models after training and recognition tests showed that driver behavior modeling and recognition of different types of lane changes is possible using HMMs.

This paper introduces a new design for alternator systems that provides dramatic increases in peak and average power output from a conventional Lundell alternator, along with substantial improvements in efficiency. Experimental results demonstrate these capability improvements. Additional performance and functionality improvements of particular value for high-voltage (e.g., 42 V) alternators are also demonstrated. Tight load-dump transient suppression can be achieved using this new design and the alternator system can be used to implement jump charging (the charging of the high-voltage system battery from a low-voltage source). Dual-output extensions of the technique (e.g., 42/14 V) are also introduced. The new technology preserves the simplicity and low cost of conventional alternator designs, and can be implemented within the existing manufacturing infrastructure.

This paper describes a post-race analysis of team KOMMIT EVT’s electric motorcycle data collected during the 2016 Pikes Peak International Hill Climb (PPIHC). The motorcycle consumed approximately 4 kWh of battery energy with an average and maximum speed of 107 km/h and 149 km/h, respectively. It was the second fastest electric motorcycle with a finishing time of 11:10.480. Data was logged of the motorcycle’s speed, acceleration, motor speed, power, currents, voltages, temperatures, throttle position, GPS position, rider’s heart rate and the ambient environment (air temperature, pressure and humidity). The data was used to understand the following factors that may have prevented a faster time: physical fitness of the rider, thermal limits of the motor and controller, available battery energy and the sprocket ratio between the motor and rear wheel.