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Improving passenger safety inside vehicle cabins requires continuously monitoring vehicle seat occupancy statuses. Monitoring a vehicle seat’s occupancy status includes detecting if the seat is occupied and classifying the seat’s occupancy type. This paper introduces an innovative non-intrusive technique that employs capacitive sensing and an occupancy classifier to monitor a vehicle seat’s occupancy status. Capacitive sensing is facilitated by a meticulously constructed capacitance-sensing mat that easily integrates with any vehicle seat. When a passenger or an inanimate object occupies a vehicle seat equipped with the mat, they will induce variations in the mat’s internal capacitances. The variations are, in turn, represented pictorially as grayscale capacitance-sensing images (CSI), which yield the feature vectors the classifier requires to classify the seat’s occupancy type.

The USDOT and the Crash Avoidance Metrics Partnership-Vehicle Safety Communications 2 (CAMP-VSC2) Consortium (Ford, GM, Honda, Mercedes, and Toyota) initiated, in December 2006, a three-year collaborative effort in the area of wireless-based safety applications under the Vehicle Safety Communications-Applications (VSC-A) Project. The VSC-A Project developed and tested communications-based vehicle safety systems to determine if Dedicated Short Range Communications (DSRC) at 5.9 GHz, in combination with vehicle positioning, would improve upon autonomous vehicle-based safety systems and/or enable new communications-based safety applications.

The United States Department of Transportation (USDOT) and the Crash Avoidance Metrics Partnership-Vehicle Safety Communications 2 (CAMP-VSC2) Consortium (Ford, General Motors, Honda, Mercedes-Benz, and Toyota) initiated, in December 2006, a three-year collaborative effort in the area of wireless-based safety applications under the Vehicle Safety Communications-Applications (VSC-A) Project. The VSC-A Project developed and tested Vehicle-to-Vehicle (V2V) communications-based safety systems to determine if Dedicated Short Range Communications (DSRC) at 5.9 GHz, in combination with vehicle positioning, would improve upon autonomous vehicle-based safety systems and/or enable new communications-based safety applications.

A computational model of a mid-size sport utility vehicle was developed using MADYMO. The model includes a detailed description of the suspension system and tire characteristics that incorporated the Delft-Tyre magic formula description. The model was correlated by simulating a vehicle suspension kinematics and compliance test. The correlated model was then used to simulate a J-turn vehicle dynamics test maneuver, a roll and non-roll ditch test, corkscrew ramp and a lateral trip test, the results of which are presented in this paper. The results indicate that MADYMO is able to reasonably predict the vehicle and occupant responses in these types of applications and is potentially suited as a tool to help setup a suite of vehicle configurations and test conditions for rollover sensor testing. A suspension system sensitivity study is presented for the laterally tripped non-roll event.

Vehicle thermal loads in sunny climates are strongly influenced by the absorption of solar thermal energy. Reduction of the absorptivity in the near infrared (IR) spectrum would decrease vehicle soak temperatures, reduce air conditioning power consumption and not affect the vehicle visible spectrum radiation properties (color). The literature [1] indicates that paint formulations with carbon-black pigment removed or reduced can be made to be reflective to near infrared frequencies. Experiments indicated that the reflectivity can be improved with existing basecoats and primers. Experiments and numerical simulations indicate that vehicle soak temperatures can be reduced by over 2 °C with existing basecoats and primers.

This paper describes the validation of RAMSIS, a 3-D CAD human model for ergonomic vehicle evaluation. At GM NAO, the model’s capability to correctly predict position and posture in vehicle CAD environments was tested. H- and Eye point locations between RAMSIS manikins and their human counterparts were compared. At GM/SAAB the model’s postural discomfort predictability was evaluated. Changes in postural discomfort predictions of the RAMSIS manikins were compared to that of the human subjects when they evaluated two different driving buck conditions. We concluded that RAMSIS has good position, posture and postural discomfort prediction capabilities and is a useful CAD ergonomic evaluation and design tool for vehicle interiors.

This paper summarizes the validation of prototype vehicle-to-infrastructure (V2I) safety applications based on Dedicated Short Range Communications (DSRC) in the United States under a cooperative agreement between the Crash Avoidance Metrics Partners LLC (CAMP) and the Federal Highway Administration (FHWA). After consideration of a number of V2I safety applications, Red Light Violation Warning (RLVW), Curve Speed Warning (CSW) and Reduced Speed Zone Warning with Lane Closure Warning (RSZW/LC) were developed, validated and demonstrated using seven different vehicles (six passenger vehicles and one Class 8 truck) leveraging DSRC-based messages from a Road Side Unit (RSU). The developed V2I safety applications were validated for more than 20 distinct scenarios and over 100 test runs using both light- and heavy-duty vehicles over a period of seven months. Subsequently, additional on-road testing of CSW on public roads and RSZW/LC in live work zones were conducted in Southeast Michigan.

Traditionally, Knee Air Bag (KAB) is constructed of a woven nylon or polyester fabric. Recently, Ford developed an injection molded air bag system for the passenger side called Active Glove Box (AGB). This system integrates a plastic bladder welded between the glove box outer and inner doors. This new system is smaller and lighter, thus improving the roominess and other creature comforts inside the passenger cabin while providing equivalent restraint performance as traditional knee airbag system. This patented technology allows positioning of airbags in new locations within the vehicle, thus giving more freedom to designers. The first application of this technology was standard equipment on the 2015 Ford Mustang. Given that this technology is first in the industry, it was a challenge to design, test and evaluate the performance of the system as there is no benchmark to compare this technology. A CAE driven design methodology was chosen to overcome this challenge.

This paper investigates the application of the Hybrid FE-SEA method to the prediction of the Transmission Loss (TL) of a front-of-dash component. SEA subsystems are used to represent the source and receiving chambers of a TL test suite and an FE structural subsystem is used to represent the dash component. The potential advantages of the Hybrid FE-SEA method for this application are that: (i) it can provide detailed narrowband predictions of the radiation efficiency and TL of a given component across a broad frequency range and (ii) the computational cost of the approach is typically several orders of magnitude less than that of traditional low frequency FE/BEM/IEM methods. The approach is also potentially well suited to existing analysis processes since information from detailed component level models can be used to update and refine targets obtained from system level SEA models (the use of a common environment for such models simplifies model management).

Vehicle idle quality has become an increasing quality concern for automobile manufacturers because of its impact on customer satisfaction. There are two factors that critical to vehicle idle quality, the engine excitation force and vehicle sensitivity (transfer function). To better understand the contribution to the idle quality from these two factors and carry out well-planned improvement measures, a quick and easy way to measure vehicle sensitivity at idle conditions is desired. There are several different ways to get vehicle sensitivity at idle conditions. A typical way is to use CAE. One of the biggest advantages using CAE is that it can separate vehicle sensitivities to different forcing inputs. As always, the CAE results need to be validated before being fully utilized. Another way to get vehicle sensitivity is through impact test using impact hammer or shaker. However this method doesn't include the mount preload due to engine firing torque [3, 4, & 5].

The ability to extract and evaluate the time history of structural deformations or crush during vehicle crashes represents a significant challenge to automotive safety researchers. Current methods are limited by the use of electro-mechanical devices such as string pots and/or linear variable displacement transducers (LVDT). Typically, one end of the transducer must be mounted to a point on the structure that will remain un-deformed during the event; the other end is then attached to the point on the structure where the deformation is to be measured. This approach measures the change in distance between these two points and is unable to resolve any movement into its respective X, Y, or Z directions. Also, the accuracy of electro-mechanical transducers is limited by their dynamic response to crash conditions. The photogrammetry technique has been used successfully in a wide variety of applications including aerial surveying, civil engineering and documentation of traffic accidents.

This paper reports a study of the dynamic characteristics of body mounts in body on frame vehicles and their effects on structural and occupant CAE results. The body mount stiffness and damping are computed from spring-damper models and component test results. The model parameters are converted to those used in the full vehicle structural model to simulate the vehicle crash performance. An effective body mount in a CAE crash model requires a set of coordinated damping and stiffness to transfer the frame pulse to the body. The ability of the pulse transfer, defined as transient transmissibility[1]1, is crucial in the early part of the crash pulse prediction using a structural model such as Radioss[2]. Traditionally, CAE users input into the model the force-deflection data of the body mount obtained from the component and/or full vehicle tests. In this practice, the body mount in the CAE model is essentially represented by a spring with the prescribed force-deflection data.

Petit et al. 2015 and Lebarbé et al. 2016 reported on two studies where the injury mechanism and threshold of the sacroiliac joint were investigated in two slightly oblique crash test conditions from 18 Post Mortem Human Subjects (PMHS) tests. They concluded that the sacroiliac joint fractures were associated with pubic rami fractures. These latter being reported to occur first in the time history. Therefore it was recommended not to define a criterion specific for the sacroiliac joint. In 2012, injury risk curves were published for the WorldSID dummy by Petitjean et al. For the pelvis, dummy and PMHS paired tests from six configurations were used (n = 55). All of these configurations were pure lateral impacts. In addition, the sacroiliac joint and femur neck loads were not recorded, and the dummy used was the first production version (WorldSID revision 1). Since that time, the WorldSID was updated several times, including changes in the pelvis area.

This paper compares the results from three human factors studies conducted in a motion-based simulator in 2008, 2014 and 2023, to highlight the trends in driver's response to Forward Collision Warning (FCW). The studies were motivated by the goal to develop an effective HMI (Human-Machine Interface) strategy that enables the required driver's response to FCW while minimizing the level of annoyance of the feature. All three studies evaluated driver response to a baseline-FCW and no-FCW conditions. Additionally, the 2023 study included two modified FCW chime variants: a softer FCW chime and a fading FCW chime. Sixteen (16) participants, balanced for gender and age, were tested for each group in all iterations of the studies. The participants drove in a high-fidelity simulator with a visual distraction task (number reading). After driving 15 minutes in a nighttime rural highway environment, a surprise forward collision threat arose during the distraction task.

Future automobiles are required to support an increasing number of complex, distributed functions such as active safety and X-by-wire. Because of safety concerns and the need to deliver correct designs in a short time, system properties should be verified in advance on function models, by simulation or model checking. To ensure that the properties still hold for the final deployed system, the implementation of the models into tasks and communication messages should preserve properties of the model, or in general, its semantics. FlexRay offers the possibility of deterministic communication and can be used to define distributed implementations that are provably equivalent to synchronous reactive models like those created from Simulink. However, the low level communication layers and the FlexRay schedule must be carefully designed to ensure the preservation of communication flows and functional outputs.

This research developed a new measurement technology for thermal analysis of the heat radiation from a hybrid transaxle case surface to the air and improved the heat radiation performance. This heat flux measurement technology provides the method to measure heat flux without wiring of sensors. The method does not have effects of wiring on the temperature field and the flow field unlike the conventional methods. Therefore, multipoint measurement of heat flux on the case surface was enabled, and the distribution of heat flux was quantified. To measure heat flux, thermal resistances made of plastic plates were attached to the case surface and the infrared thermography was used for the temperature measurement. The preliminary examination was performed to confirm the accuracy of the thermal evaluation through heat flux measurement. The oil in the transaxle was heated and the amount of heat radiation from the case surface was measured.

This paper proposes a theory to analyze the collision avoidance capability of automated driving technologies. The theory gives answers to a fundamental question whether automated vehicles fall into extreme conditions at all rather than another question how a vehicle reacts under extreme conditions (is it as safe as driver?). The theory clarifies the following matters: There are two types of hazards to cause collisions, cognitive hazards and behavioral hazards. Cognitive hazards are handled by controlling the upper limit speed of the automated vehicle including when stopped. There are two methods for handling behavioral hazards, preparation and response. The response known well is the coping method activated when the hazard is detected in the dynamic (operational) level. The preparation is the coping method operating at all time in the semantic (tactical) level.

During the early phase of vehicle development, one of the key design attributes to consider is visibility for the driver. Visibility is the ability to see the surrounding environment as one is driving. This need should drive the vehicle design enabling a move favorable view for the driver. Certain vehicle characteristics such as the size of windshield and the design of the pillar influence the perception of visibility for the driver. One specific characteristic influencing satisfaction is forward up vision, which is the subject of this paper. The objective of this project was to analyze the influence of forward up vision on driver satisfaction under real world driving conditions. Other influences such as the positon of the occupant in the seat was also studied. This study was supported by research, statistical data analysis and dynamic clinics.

During the early phase of vehicle development, one of the key design attributes to consider is visibility for the driver. Visibility is the ability to see one’s surrounding environment while they are driving. Therefore, it is one of the key requirements to be considered during the vehicle design. Certain vehicle characteristics such as the size of windshield and the design of the pillars influence the perception of visibility for the driver. One specific characteristic influencing satisfaction is A-pillar obscuration and location, which is the subject of this paper. The objective of this project is to analyze the relationship between the A-pillar obscuration/location with the driver satisfaction under real world driving conditions, based on research, statistical data analysis and dynamic clinics. Other influences, such as the position of the occupant in the seat was also studied and captured in this paper.

In an evaluation of crashworthiness for the cars made of aluminum alloys, the evaluation considering fracture phenomenon comes to be needed because conventional aluminum alloys have low fracture strain (10-20%). In case of the development of a B-Pillar made by die cast, if crack occurrence, furthermore, separation of a part can be estimated by using CAE in crashworthiness evaluations, we can reduce the number of prototype makings and the cost of development using expensive dies. Therefore, we performed crashworthiness evaluations by CAE using some sort of a damage & fracture material model. It is known as “Orthotropic damage & fracture model”.