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The development of a repeatable dynamic rollover test methodology with meaningful occupant protection performance objectives has been a longstanding and unmet challenge. Numerous studies have identified the random and chaotic nature of rollover crashes, and the difficulty associated with simulating these events in a laboratory setting. Previous work addressed vehicle level testing attempting to simulate an entire rollover event but it was determined that this test methodology could not be used for development of occupant protection restraint performance objectives due to the unpredictable behavior of the vehicle during the entire rollover event. More recent efforts have focused on subsystem tests that simulate distinct phases of a rollover event, up to and including the first roof-to-ground impact.

Finite element dummy models have been more and more widely applied in virtual development of occupant protection systems across the automotive industry due to their predictive capabilities. H350 dyna dummy model [1] is a finite element representation of the Hybrid III male dummy [2], which is designed to represent the average of the United States adult male population. Lower extremity injuries continue to occur in front crash accidents despite increasing improvement of vehicle crashworthiness and occupant restraint system. It is therefore desirable to predict lower tibia injury numbers in front occupant simulations. Though lower tibia loading/index predictions are not studied as much as the FMVSS 208 regulated injury numbers, the tibia indices are injury criteria that need to be assessed during IIHS and Euro NCAP frontal offset occupant simulations. However during front crash simulations, it is very difficult to achieve good correlations or predictions of lower tibia loadings.

Impact toughness (or resistance to fracture) is a key material property for press hardened steel used in construction of the safety-critical elements of automotive body structures. Prior austenite grain size, as primarily controlled by the incoming microstructure and austenitization process, is a key microstructural feature that influences the impact toughness of press hardened steel. In this paper, a special Charpy V-notch impact test is developed to quantify the impact toughness of press hardened steel sheets with various prior austenite grain sizes, by stacking a number of thin sheets via mechanical riveting. Both the ductile-to-brittle transition temperature and upper shelf energy are analyzed in an effort to establish a correlation between impact toughness and prior austenite grain size. Within tested conditions, impact performance shows only a slight decrease as the prior austenitic grain size increases from 18 to 38 microns.

As the new features for driver assistance and active safety systems are growing rapidly in vehicles, the simulation within a virtual environment has become a necessity. The current active safety system consists of Electronic Control Units (ECUs) which are coupled to camera and radar sensors. Two methods of implementation exists, integrated sensors with control modules or separation of sensors form control modules. The subsystem integration testing poses new challenges for virtual environment for simulation of active safety features. The comprehensive simulation environment for integration testing consists of chassis controls, powertrain, driver assistance, body and displays controllers. Additional complexity in the system is the serial communication strategy. Multiple communication protocols such as GMLAN, LIN, standard CAN, and Flexray could be present within the same vehicle topology.

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.

An analysis of the first 35 back-over crashes reported by NHTSA's Special Crash Investigations unit was undertaken with two objectives: (1) to test a hypothesized classification of backing crashes into types, and (2) to characterize scenario-specific conditions that may drive countermeasure development requirements and/or objective test development requirements. Backing crash cases were sorted by type, and then analyzed in terms of key features. Subsequent modeling of these SCI cases was done using an adaptation of the Driving Reliability and Error Analysis Methodology (DREAM) and Cognitive Reliability and Error Analysis Methodology (CREAM) (similar to previous applications, for instance, by Ljung and Sandin to lane departure crashes [10]), which is felt to provide a useful tool for crash avoidance technology development.

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.

Forward Collision Alert (or Forward Collision Warning) systems provide alerts intended to assist drivers in avoiding or mitigating the harm caused by rear-end crashes. These systems currently use front-grille mounted, forward-looking radar devices as the primary sensor. In contrast, Lane Departure Warning (LDW) systems employ forward-looking cameras mounted behind the windshield to monitor lane markings ahead and warn drivers of unintended lane violations. The increasing imaging sensor resolution and processing capability of forward-looking cameras, as well recent important advances in machine vision algorithms, have pushed the state-of-the-art for camera-based features. Consequently, camera-based systems are emerging as a key crash avoidance system component in both a primary and supporting sensing role. There are currently no production vehicles with cameras used as the sole FCA sensing device.

Vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications are gaining increasing importance in automotive research and engineering domains. The novel communication scheme is targeted to improve driver safety (e.g., forward collision warnings) and comfort (e.g., routing to avoid congestion, automatic toll collection, etc.). Features exploiting these communication schemes are still in the early stages of research and development. However, growing attention to system wide infrastructure - in terms of OEM collaboration on interface standardization, protocol standardization, and government supported road/wireless infrastructure - will lead to popularity of such features in the future. This paper focuses on evaluating reliability and safety/integrity of data communicated over the wireless channels for early design verification. Analysis of a design can be done based on formal models, simulation, emulation, and testing.

The primary function of an airbag control module is to detect crashes, discriminate and predict if a deployment is necessary, then deploy the restraint systems including airbags and where applicable, pretensioners. At General Motors (GM), the internal term for airbag control module is Sensing and Diagnostic Module (SDM). In the 1994 model year, GM introduced its SDM on some of its North American airbag-equipped vehicles. A secondary function of that SDM and all subsequent SDMs is to record crash related data. This data can include data regarding impact severity from internal accelerometers and pre-crash vehicle data from various chassis and powertrain modules. Previous researchers have addressed the accuracy of both the velocity change data, recorded by the SDM, and the pre-crash data, but the assessment of the timing of the pre-crash data has been limited to a single family of modules (Delphi SDM-G).

Incomplete vehicles are partially manufactured by an Original Equipment Manufacturer (OEM) and subsequently sold to and completed by a final-stage manufacturer. Section S8.8, Final-Stage Manufacturers and Alterers, of Federal Motor Vehicle Safety Standard (FMVSS) 126 states “Vehicle that are manufactured in two or more stages or that are altered (within the meaning of 49 CFR 567.7) after having been previously certified in accordance with Part 567 of this chapter, are not subject to the requirements of S8.1 through S8.5. Instead, all vehicles produced by these manufacturers on or after September 1, 2012, must comply with this standard.” The FMVSS 126 compliance of the completed vehicle can be certified in three ways: by the OEM provided no alterations are made to identified components (TYPE 1), conditionally by the OEM provided the final-stage manufacturer follows specific guidelines (TYPE 2), or by the final-stage manufacturer (TYPE 3).

This study concerns the generation of response surfaces for kinematics and injury prediction in pedestrian impact simulations using human body model. A 1000-case DOE (Design of Experiments) study with a Latin Hypercube sampling scheme is conducted using a finite element pedestrian human body model and a simplified parametric vehicle front-end model. The Kriging method is taken as the approach to construct global approximations to system behavior based on results calculated at various points in the design space. Using the response surface models, human lower limb kinematics and injuries, including impact posture, lateral bending angle, ligament elongation and bone fractures, can be quickly assessed when either the structural dimensions or the structural behavior of the vehicle front-end design change. This will aid in vehicle front-end design to enhance protection of pedestrian lower limbs.

Although the measured amount of roof deformation associated with a given rollover crash test is often the residual or post test deformation, rollover crash test researchers are aware that roof deformation occurs dynamically throughout the rollover event with varying magnitude. The challenge to quantifying dynamic roof deformation has been the lack of a reliable method to measure and record the dynamic roof deformation during the rollover test. Researchers have explored various methods to measure dynamic roof deformation including the use of film analysis of external targets, accelerometers, string potentiometers, and 3D photogrammetry. This paper discusses a series of simulated curb trip rollover tests conducted to study and compare different methodologies to measure and record dynamic roof deformation.

In 2006, the Insurance Institute for Highway Safety (IIHS) released a new Low Speed Bumper Test Protocol for passenger cars1. The new test protocol included the development of a deformable barrier that the vehicle would impact at low speeds. IIHS positioned the new barrier to improve correlation to low speed collisions in the field, and also to assess the ability of the bumper system to protect the vehicle from damage. The bumper system must stay engaged to the barrier to protect other vehicle components from damage. The challenge is to identify the bumper system design features that minimize additional cost and mass to keep engagement to the barrier. The results of the Design for Six Sigma analysis identified the design features that increase the stiffness of the bumper system enable it to stay engaged to the barrier and reduce the deflection.

This paper attempts to integrate a derivative-free probability analysis method to Reliability-Based Robust Design Optimization (RBRDO). The Eigenvector Dimension Reduction (EDR) method is used for the probability analysis method. It has been demonstrated that the EDR method is more accurate and efficient than the Second-Order Reliability Method (SORM) for reliability and quality assessment. Moreover, it can simultaneously evaluate both reliability and quality without any extra expense. Two practical engineering problems (vehicle side impact and layered bonding plates) are used to demonstrate the effectiveness of the EDR method.

In the last decade, considerable advances have been made in reliability-based design optimization (RBDO). One assumption in RBDO is that the complete information of input uncertainties are known. However, this assumption is not valid in practical engineering applications, due to the lack of sufficient data. In practical engineering design, information concerning uncertainty parameters is usually in the form of finite samples. Existing methods in uncertainty based design optimization cannot handle design problems involving epistemic uncertainty with a shortage of information. Recently, a novel method referred to as Bayesian Reliability-Based Design Optimization (BRBDO) was proposed to properly handle design problems when engaging both epistemic and aleatory uncertainties [1]. However, when a design problem involves a large number of epistemic variables, the computation task for BRBDO becomes extremely expensive.

This paper presents an innovative approach for quality engineering using the Eigenvector Dimension Reduction (EDR) Method. Currently industry relies heavily upon the use of the Taguchi method and Signal to Noise (S/N) ratios as quality indices. However, some disadvantages of the Taguchi method exist such as, its reliance upon samples occurring at specified levels, results to be valid at only the current design point, and its expensiveness to maintain a certain level of confidence. Recently, it has been shown that the EDR method can accurately provide an analysis of variance, similar to that of the Taguchi method, but is not hindered by the aforementioned drawbacks of the Taguchi method. This is evident because the EDR method is based upon fundamental statistics, where the statistical information for each design parameter is used to estimate the uncertainty propagation through engineering systems.

More and more advanced features such as adaptive cruise control and collision avoidance are being adopted in road vehicles and these features are usually implemented as distributed systems across multiple ECU nodes that are connected by communication busses. In order to tolerate transient faults affecting a safety critical signal transmitted via bus in such distributed systems, the last used value or a default safe value for a safety critical signal is usually used among different ECU nodes on the bus for a pre-defined time interval before taking some other fault mitigation actions such as disabling a feature. Thus it becomes very important to monitor a signal's age and detect any signal age fault, where a signal age fault is defined as the use of an older or default signal value for longer than or equal to the pre-defined time interval.

Accurate prediction of the responses from the anthropomorphic test devices (ATDs) in vehicle crash tests is critical to achieving better vehicle occupant performances. In recent years, automakers have used finite element (FE) models of the ATDs in computer simulations to obtain early assessments of occupant safety, and to aid in the development of occupant restraint systems. However, vehicle crash test results have variation, sometimes significant. This presents a challenge to assessing the accuracy of the ATD FE models, let alone improving them. To resolve this issue, it is important to understand the test variation and carefully select the target data for model improvement. This paper presents the work carried out by General Motors and Humanetics Innovative Solutions (formerly FTSS) in a joint project, aimed at improving the FE model of the Hybrid III-50 ATD (HIII-50) v5.1.

This study documents a method developed for dynamically measuring occupant pocketing during various low-speed rear impact, or “whiplash” sled tests. This dynamic pocketing measurement can then be related to the various test parameters used to establish the performance rating or compliance results. Consumer metric and regulatory tests discussed within this paper as potential applications of this technique include, but are not limited to, the Insurance Institute for Highway Safety (IIHS) Low Speed Rear Impact (LSRI) rating, Federal Motor Vehicle Safety Standard (FMVSS) 202a, and European New Car Assessment Program (EURO-NCAP) whiplash rating. Example metrics are also described which may be used to assist in establishing the design position of the head restraint and optimize the balance between low-speed rear impact performance and customer comfort.