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Driver distraction is a topic of considerable interest, with the public debate centering on the use of cell phones and texting while driving. However, the driver distraction/overload issue is really much larger. It concerns specific tasks such as entering destinations on navigation systems, retrieving songs on MP3 players, accessing web pages, checking stocks, editing spreadsheets, and performing other tasks on smart phones, as well as, more generally, using in-vehicle information systems. Five major problems related to distraction/overload research and engineering and their solutions are addressed in this paper.

This study was designed to investigate how the spectral power distribution (SPD) of LED headlamps (including correlated color temperature, CCT) affects both objective driving performance and subjective responses of drivers. The results of this study are not intended to be the only considerations used in choosing SPD, but rather to be used along with results on how SPD affects other considerations, including visibility and glare. Twenty-five subjects each drove 5 different headlamps on each of 5 experimental vehicles. Subjects included both males and females, in older (64 to 85) and younger (20 to 32) groups. The 5 headlamps included current tungsten-halogen (TH) and high-intensity discharge (HID) lamps, along with three experimental LED lamps, with CCTs of approximately 4500, 5500, and 6500 K. Driving was done at night on public roads, over a 21.5-km route that was selected to include a variety of road types.

Available methodologies for model bias identification are mainly regression-based approaches, such as Gaussian process, Bayesian inference-based models and so on. Accuracy and efficiency of these methodologies may degrade for characterizing the model bias when more system inputs are considered in the prediction model due to the curse of dimensionality for regression-based approaches. This paper proposes a copula-based approach for model bias identification without suffering the curse of dimensionality. The main idea is to build general statistical relationships between the model bias and the model prediction including all system inputs using copulas so that possible model bias distributions can be effectively identified at any new design configurations of the system. Two engineering case studies whose dimensionalities range from medium to high will be employed to demonstrate the effectiveness of the copula-based approach.

Over half of the greenhouse gas (GHG) emissions in the United States come from the transportation and electricity generation sectors. To analyze the potential impact of cross-sector cooperation in reducing these emissions, we formulate a bi-level optimization model where the transportation sector can purchase renewable energy certificates (REC) from the electricity generation sector. These RECs are used to offset emissions from transportation in lieu of deploying high-cost fuel efficient technologies. The electricity generation sector creates RECs by producing additional energy from renewable sources. This additional renewable capacity is financed by the transportation sector and it does not impose additional cost on the electricity generation sector. Our results show that such a REC purchasing regime significantly reduces the cost to society of reducing GHG emissions. Additionally, our results indicate that a REC purchasing policy can create electricity beyond actual demand.

A new generation of a planetary-gear-based automatic transmission system is designed with an increasing number of ratio steps. It requires synchronous operation of one or more wet clutches, to achieve a complex shift event. A missed synchronization results in drive torque disturbance which may be perceived by vehicle occupants as an undesirable shift shock. Accurate knowledge of clutch behaviors in an actual vehicle environment is indispensable for achieving precise clutch controls and reducing shift calibration effort. Wet clutches are routinely evaluated on an industry-standard SAE#2 tester during the clutch design process. While it is a valuable tool for screening relative frictional behaviors, clutch engagement data from a SAE#2 tester do not correlate well with vehicle shift behaviors due to the limited reproducibility of realistic slip, actuator force profiles, and lubrication conditions.

Ball nut assemblies (BNAs) are used in a variety of applications, e.g., automotive, aerospace and manufacturing, for converting rotary motion to linear motion (or vice versa). In these application areas, accurate characterization of the dynamics of BNAs using low-order models is very useful for performance simulation and analyses. Existing low-order contact load models of BNAs are inadequate, partly because they only consider the axial deformations of the screw and nut. This paper presents a low-order load distribution model for BNAs which considers the axial, torsional and lateral deformations of the screw and nut. The screw and nut are modeled as finite element beams, while Hertzian Contact Theory is used to model the contact condition between the balls and raceways of the screw and nut. The interactions between the forces and displacements of the screw and nut and those at the ball-raceway contact points are established using transformation matrices.

Lean NOx Traps (LNTs) are one type of lean NOx reduction technology typically used in smaller diesel passenger cars where urea-based Selective Catalytic Reduction (SCR) systems may be difficult to package . However, the performance of lean NOx traps (LNT) at temperatures above 400 C needs to be improved. The use of Rapidly Pulsed Reductants (RPR) is a process in which hydrocarbons are injected in rapid pulses ahead of a LNT in order to expand its operating window to higher temperatures and space velocities. This approach has also been called Di-Air (diesel NOx aftertreatment by adsorbed intermediate reductants) by Toyota. There is a vast parameter space which could be explored to maximize RPR performance and reduce the fuel penalty associated with injecting hydrocarbons. In this study, the mixing uniformity of the injected pulses, the type of reductant, and the concentration of pulsed reductant in the main flow were investigated.

Most current applications of digital human figure models for ergonomic assessments of manual tasks focus on the analysis of a static posture. Tools available for static analysis include joint-specific strength, calculation of joint moments, balance maintenance capability, and low-back compression or shear force estimates. Yet, for many tasks, the inertial loads due to acceleration of body segments or external objects may contribute significantly to internal body forces and tissue stresses. Due to the complexity of incorporating the dynamics of motion into analysis, most commercial software packages used for ergonomic assessment do not have the capacity to include dynamic effects. Thus, commercial human modeling packages rarely provide an opportunity for the user to determine if a static analysis is sufficient.

Exposure of a driver to vehicle vibration is known to disrupt manual performances, and more specifically affect the speed and accuracy of reaching tasks associated with vehicle operation. The effects of whole body vibration (WBV) can be analyzed as a function of the vibration characteristics of each body link. This information can then be used to identify movement strategies and predict biodynamic responses. Conceptual principles derived from the understanding of human behavior in a vibratory environment can then be used for the design of controls or interfaces adapted for vehicle operation in this context. The transfer functions of individual upper body links were estimated to investigate their biodynamic properties as a function of vehicle vibration frequency and spatial location of targets to be reached. In the present study, fourteen seated participants performed pointing movements to eight targets distributed in the right hemisphere.

Industrial tasks performed by standing workers are among those most commonly simulated using digital human models. Workers often walk, turn, and take acyclic steps as they perform these tasks. Current h uman modeling tools lack the capability to simulate these whole body motions accurately. Most models simulate walking by replaying joint angle trajectories corresponding to a general gait pattern. Turning is simulated poorly if at all, and violations of kinematic constraints between the feet and ground are common. Moreover, current models do not accurately predict foot placement with respect to loads and other hand targets, diminishing the utility of the associated ergonomic analyses. A new approach to simulating stepping and walking in task-oriented activities is proposed. Foot placements and motions are predicted from operator and task characteristics using empirical models derived from laboratory data and validated using field data from an auto assembly plant.

The pulleys employed in automotive accessory drive systems very often consist of a two piece assembly; a multitude of fastening techniques are used in completing the assembly. There are numerous assembly methods and a variety of distinct pulley configurations dictated by the various automobile manufacturers in accordance with individual accessory drive needs. An expert system is being developed to evaluate the merit of multiple assembly alternatives for a specific pulley application. The expert system provides a consistent evaluation tool for assembly alternatives, balancing the influence of product cost, strength and quality considerations. The knowledge-based system is implemented in an expert system shell called AGNESS (A Generalized Network-based Expert System Shell). The expert system judges the acceptability of various pulley assembly techniques, assigning a high “merit value” to the better designs and proportionately lower values to less desirable designs.

Half of the car occupant deaths involved in two-vehicle crashes results from side impact collisions. In an attempt to better understand the role that vehicle mass plays in crashes and injury causation, detailed information from the NASS CDS database on injury source was distributed in three classes: contact with intrusion, contact without intrusion, and restrained acceleration or non-contact. We compared these distributions for belted drivers in side verses frontal crashes. When looking at the type of striking, or bullet, vehicle in near-side impacts, we found that intrusion injuries are more prevalent in cars hit by SUVs and pickups than by other cars. We also looked at the body region injured verses the type of striking vehicle and found head injuries to be slightly more prevalent when the striking vehicle is an SUV or pick-up. Data from the University of Michigan CIREN case studies on side impacts are presented and are consistent with the NASS CDS data.

Many highway accidents are caused by distracted drivers and those suffering from drowsy driver syndrome. A driver alert indicating a lane departure could thwart such accidents, saving lives and making our roads safer. Products called Lane Departure Warning Systems (LDWS) have been developed to alert drivers of a lane departure. However, due to their high cost, lane departure warning systems are available only on luxury vehicles, barring their benefits from the majority of drivers. With Field Programmable Gate Arrays (FPGA) becoming more powerful and more affordable, a LDWS implementation utilizing hardware rather than software to conduct image processing eliminates the need for a costly high-power microprocessor, and could bring LDWS to a broader user base. This paper will discuss an FPGA based approach to LDWS. The proof-of-concept system is based on a Xilinx FPGA, taking its image data from an off-the-shelf NTSC camera.

Thermal distortions of friction disks caused by frictional heating modify pressure distribution on friction surfaces. Pressure distribution, in turn, determines distribution of generated frictional heat. These interdependencies create a complex thermoelastic system that, under some conditions, may become unstable and may lead to severe pressure concentrations with very high local temperature and stress. The phenomenon is responsible for many common thermal failure modes of friction elements and is known as frictionally excited thermoelastic instability (TEI). In the paper, one of the cases of TEI is investigated theoretically and experimentally. The study involves a two-disk structure with one fiction disk and one matching steel disk that have one friction interface. An unsteady heat conduction problem and an elastic contact problem are modeled as axisymmetric ones and are solved using the finite element method.

While the results are generally the most exciting aspects of an LCI study, the details of the LCI model that generates the results are equally significant; particularly when modeling the life cycle of an automobile. The modeling challenges faced in conducting the US AMP LCI of a mid-sized vehicle based on the 1995 Lumina, Intrepid and Taurus are highlighted. The number of parts (over 20,000), supply chain complexity, materials composition, and the demanding set of OEM requirements for model features required special LCI methods and solutions. The LCI model and selected results are compared with previous studies, and recommendations for improvements in the USAMP LCI model are also provided. This paper is one of six SAE publications discussing the results and execution of the USCAR AMP Generic Vehicle LCI. The papers in this series are (Overview of results 982160, 982161, 982162, 982168, 982169, 982170).

The chance of vehicle collisions significantly increases when drivers are overloaded with information from in-vehicle systems. Developing adaptive workload management systems (AWMS) to dynamically control the rate of messages from these in-vehicle systems is one of the solutions to this problem. However, existing AWMSs do not use a model of driver cognitive system to estimate workload and only suppress or redirect in-vehicle system messages, without changing their rate based on driver workload. In this work, we propose a prototype of a new adaptive workload management system (QN-MHP AWMS) and it includes: a queueing network model of driver workload (Wu & Liu, In Press) that estimates driver workload in different driving situations, and a message controller that determines the optimal delay times between messages and dynamically controls the rate of messages presented to drivers.

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.

Simulation of reach movements is an essential component for proactive ergonomic analysis in digital human modeling and for numerous applications in vehicle design. Most studies on reach kinematics described human movements in static conditions. Earlier studies of reach performance in vibration environments focused mainly on fingertip deviation without considering multi-body dynamics. However, for the proper assessment of reach performance under whole-body vibration exposure, a multi-body biodynamic model needs to be developed. This study analyzes three dimensional reach kinematics of the upper extremity during in-vehicle operations, using a multi-segmental model of the upper body in the vibratory environment. The goals are to identify the characteristics of upper body reach movements and to investigate vibration-induced changes in joint kinematics. Thirteen subjects reached to four target directions in the right hemisphere.

This paper investigates how reaching and grasping are affected by various object properties and conditions. While previous studies have examined the effect of object attributes such as size, shape, and distance from the subject, there is a need for quantitative models of finger motions. To accomplish this, the experiment was performed with six subjects where the 3D-coordinates of the finger joints and the wrist of one hand were recorded during reaching and grasping tasks. Finger joint angles at final posture were found to depend on both object size and orientation while wrist postures were changed primarily depending on object orientation. Also, each object orientation caused alteration in relative object location with respect to the hand at final posture. In addition, analysis of temporal variables revealed that it took from 1.06 to 1.30 seconds depending on the object distance to start reaching and complete grasping of the object.

A research scheme and preliminary results of a pilot study concerning upper body coordination in reach movements is presented. Techniques for multi-joint arm movements were used to obtain the kinematics of each body segment in reach movements to targets spatially distributed in a horizontal plane. Further understanding of the control mechanisms associated with coordination is investigated by combining the information of gaze orientation and body segment movements during reach activities. The implicit sequence of body segments in reach movement can be derived from their kinematic characteristics. Moreover, an identification of phases composing a reach movement is attempted.