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We propose a composite thermal model of the vehicle passenger compartment that can be used to predict and analyze thermal comfort of the occupants of a vehicle. Physical model is developed using heat flow in and out of the passenger compartment space, comprised of glasses, roof, seats, dashboard, etc. Use of a model under a wide variety of test conditions have shown high sensitivity of compartment air temperature to changes in the outside air temperature, solar heat load, temperature and mass flow of duct outlet air from the climate control system of a vehicle. Use of this model has subsequently reduced empiricism and extensive experimental tests for design and tuning of the automatic climate control system. Simulation of the model allowed several changes to the designs well before the prototype hardware is available.

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.

This paper quantifies the potential of electric propulsion systems to reduce petroleum use and greenhouse gas (GHG) emissions in the 2030 U.S. light-duty vehicle fleet. The propulsion systems under consideration include gasoline hybrid-electric vehicles (HEVs), plug-in hybrid vehicles (PHEVs), fuel-cell hybrid vehicles (FCVs), and battery-electric vehicles (BEVs). The performance and cost of key enabling technologies were extrapolated over a 25-30 year time horizon. These results were integrated with software simulations to model vehicle performance and tank-to-wheel energy consumption. Well-to-wheel energy and GHG emissions of future vehicle technologies were estimated by integrating the vehicle technology evaluation with assessments of different fuel pathways. The results show that, if vehicle size and performance remain constant at present-day levels, these electric propulsion systems can reduce or eliminate the transport sector's reliance on petroleum.

A relationship between the risk of significant thoracic injury (AIS ≥ 3) and Hybrid III dummy sternal deflection for shoulder belt loading is developed. This relationship is based on an analysis of the Association Peugeot-Renault accident data of 386 occupants who were restrained by three-point belt systems that used a shoulder belt with a force-limiting element. For 342 of these occupants, the magnitude of the shoulder belt force could be estimated with various degrees of certainty from the amount of force-limiting band ripping. Hyge sled tests were conducted with a Hybrid III dummy to reproduce the various degrees of band tearing. The resulting Hybrid III sternal deflections were correlated to the frequencies of AIS ≥ 3 thoracic injury observed for similar band tearing in the field accident data. This analysis indicates that for shoulder belt loading a Hybrid III sternal deflection of 50 mm corresponds to a 40 to 50% risk of an AIS ≥ 3 thoracic injury.

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.

A methodology involving Design for Six Sigma (DFSS) and Multi-body dynamic simulation is employed to tune a body-on-frame vehicle, for improved ride (shake) performance. The design space is limited to four sets of symmetric body mounts for a vehicle. The stiffness and damping characteristics of the mounts are the control factors in the virtual experiment. Variation of these design parameters from the nominal settings, as well as axle size, tire and wheel combinations, tire pressure, shock damping, and vehicle speed constitute the noise factors. This approach proves to be an excellent predictor of the vehicle behavior, by which much insight as to influence of each parameter on vehicle performance is gained. Ultimately, specific recommendations for the control factor settings are provided. Subsequent hardware builds show excellent agreement with the analytical model and suggested tuning.

This paper assesses the potential improvement of automotive powertrain technologies 25 years into the future. The powertrain types assessed include naturally-aspirated gasoline engines, turbocharged gasoline engines, diesel engines, gasoline-electric hybrids, and various advanced transmissions. Advancements in aerodynamics, vehicle weight reduction and tire rolling friction are also taken into account. The objective of the comparison is the potential of anticipated improvements in these powertrain technologies for reducing petroleum consumption and greenhouse gas emissions at the same level of performance as current vehicles in the U.S.A. The fuel consumption and performance of future vehicles was estimated using a combination of scaling laws and detailed vehicle simulations. The results indicate that there is significant potential for reduction of fuel consumption for all the powertrains examined.

In response to the TREAD act of 2002, ASTM F09.30 Aged Tire Durability Task Group was formed with the objective of developing a scientifically valid, short duration aged durability test which correlates to field behavior. The target end-of-test condition was belt edge separation (or related damage). One strategy, driven by that objective, has been a steady state design of experiment investigating aging temperature and duration as well as roadwheel speed, pressure and deflection. The rationale behind investigating a steady state test and selecting these parameters and methodology for setting their initial values is reviewed.

In response to the TREAD act of 2002, ASTM F09.30 Aged Tire Durability Task Group was formed with the objective of developing a scientifically valid, short duration, laboratory aged tire durability test which correlates to field behavior. The target end-of-test condition was belt edge separation (or related damage). Two strategies have been investigated, aged stepped-up load and steady state DOE. Results of the two strategies are compared and contrasted and a test condition from the steady state DOE has been identified as the preferred direction for further validation.

In the work leading to the TREAD Act, some members of Congress expressed the need for some type of aging test on light vehicle tires. Since no industry-wide recommended practice existed, the ASTM F09.30 Aged Tire Durability task group was established in 2002 to develop a scientifically valid, short duration, laboratory aged tire durability test which correlates to in-service aging. The target end-of-test condition was belt edge separation (or related tire conditions). One strategy, driven by that objective, has been a Steady State DOE investigating aging temperature and duration, as well as, roadwheel speed, pressure and deflection. Testing was performed on three tire types, including two where relevant field aging data was publicly available from NHTSA studies. A region of interest, within the design space, was identified where target end-of-test conditions were possible and undesirable (non-target or non-representative of those seen in consumer use) were avoided.

The free-rolling cornering, straight-line braking, and pull force properties of a small sample of tire specifications is examined. This is done to examine potential differences between the specifications and the statistics of force and moment measurements. Two steer axle specifications, two drive axle specifications, and a trailer specification are considered, In addition, the evolution of properties for one drive axle specification is followed from new to naturally worn-out to retreaded. The summarized data is available from SAE Cooperative Research on electronic media.

In order to engineer Squeak & Rattle (S&R) free vehicles it is essential to develop an objective measurement method to compare and correlate with customer satisfaction and subjective S&R assessments. Three methods for exciting S&Rs -type surfaces. Excitation methods evaluated were road tests over S&R surfaces, road simulators, and direct body excitation (DBE). The principle of DBE involves using electromagnetic shakers to induce controlled, road-measured vibration into the body, bypassing the tire patch and suspension. DBE is a promising technology for making objective measurements because it is extremely quiet (test equipment noise does not mask S&Rs), while meeting other project goals. While DBE is limited in exposing S&Rs caused by body twist and suspension noises, advantages include higher frequency energy owing to electro-dynamic shakers, continuous random excitation, lower capital cost, mobility, and safety.

NASA has long recognized the advantages of providing improved information interfaces to EVA astronauts and has pursued this goal through a number of development programs over the past decade. None of these activities or parallel efforts in industry and academia has so far resulted in the development of an operational system to replace or augment the current extravehicular mobility unit (EMU) Display and Controls Module (DCM) display and cuff checklist. Recent advances in display, communications, and information processing technologies offer exciting new opportunities for EVA information interfaces that can better serve the needs of a variety of NASA missions. Hamilton Sundstrand Space Systems International (HSSSI) has been collaborating with Simon Fraser University and others on the NASA Haughton Mars Project and with researchers at the Massachusetts Institute of Technology (MIT), Boeing, and Symbol Technologies in investigating these possibilities.

By design, frontal New Car Assessment Program (NCAP) tests focus on a narrow portion of the spectrum of field crash events. A simple, high level parsing of towaway crashes from NHTSA's National Automotive Sampling System - Crashworthiness Data System (NASS-CDS) files shows that only a small fraction of occupants (but a somewhat larger portion of their harm as measured by ISS) find themselves in crash circumstances remotely similar to NCAP crash conditions. Looking only at seat location, area of damage, direction of force, distribution of damage, and estimated delta-V filters significantly restricts the relevance of NCAP even before critical factors like belt use and vehicle crash partner are considered. Given the limited scope of frontal NCAP it should not be surprising that it has limited usefulness in discriminating among various vehicles' overall performance in the field.

Many traffic collisions are the result of the driver's failure to notice the other vehicle. It is often cited in police reports that the driver "looked but did not see.'' The purpose of Daytime Running Lights (DRLs) is to increase the visual contrast of DRL-equipped vehicles. Visual contrast, which is the difference in brightness between two areas, is an important characteristic enabling a driver to detect objects. This paper begins with a brief regulatory history of DRLs in the U.S. and how General Motors Corporation (GM) introduced DRL-equipped vehicles. It also describes a DRL effectiveness study conducted by Exponent Failure Analysis Associates of San Francisco for General Motors Corporation. The study compared the collision rates of specific General Motors Corporation, Saab, Volvo and Volkswagen vehicles before and immediately after the introduction of DRLs. Since DRLs are not visible from behind a vehicle, rear-end collisions were not included in the study.

Computer simulation of extravehicular activity (EVA) is increasingly being used in planning and training for EVA. A space suit model is an important, but often overlooked, component of an EVA simulation. Because of the inherent difficulties in collecting angle and torque data for space suit joints in realistic conditions, little data exists on the torques that a space suit’s wearer must provide in order to move in the space suit. A joint angle and torque database was compiled on the Extravehicular Maneuvering Unit (EMU), with a novel measurement technique that used both human test subjects and an instrumented robot. Using data collected in the experiment, a hysteresis modeling technique was used to predict EMU joint torques from joint angular positions. The hysteresis model was then applied to EVA operations by mapping out the reach and work envelopes for the EMU.

This study examined whether the effect of subsidiary tasks on driving performance can be predicted from stationary (static) testing. Alternative methods for assessing the performance of drivers during their use of in-vehicle information systems were examined. These methods included static testing in stationary vehicles, as well as dynamic, on-road testing. The measures that were obtained from static tests were evaluated in terms of how well they could predict measures obtained from driving performance during on-road testing (which included concurrent use of secondary information systems). The results indicated that measures obtained in static test settings were highly correlated with corresponding measures obtained from on-road performance testing.

The development and application of a traction control Kodiak and GMC TopKick are explained. Most traction systems use engine management to enable traction control, while the adaptive braking system can provide traction assist for either gas or Diesel powered vehicles from 14,000 lbs. to 33,000 lbs. GVW. The performance driven criteria that established the design requirements and the development of a new product to meet these objectives are discussed. Both the vehicle manufacturer and the traction controller supplier provided these criteria. The basic ABS and traction control hydraulic schematics will be described as they apply to the vehicles. The results of the development program will be compared to the criteria used to establish the goals, and the benefits of the traction control system will be discussed.

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.