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The objective of this study is to develop a method that uses a combination of field data analysis, naturalistic driving data analysis, and computational simulations to explore the potential injury reduction capabilities of integrating passive and active safety systems in frontal impact conditions. For the purposes of this study, the active safety system is actually a driver assist (DA) feature that has the potential to reduce delta-V prior to a crash, in frontal or other crash scenarios. A field data analysis was first conducted to estimate the delta-V distribution change based on an assumption of 20% crash avoidance resulting from a pre-crash braking DA feature. Analysis of changes in driver head location during 470 hard braking events in a naturalistic driving study found that drivers’ head positions were mostly in the center position before the braking onset, while the percentage of time drivers leaning forward or backward increased significantly after the braking onset.

Two rigid rollover test devices were constructed to have the approximate dimensions, mass and inertial properties of a mid-sized Car and Sport Utility Vehicle (SUV). The rigid devices were used to generate vehicle and occupant responses from a series of laboratory rollover tests. For each rigid rollover test, a deceleration sled was used to subject each rigid vehicle to nearly identical lateral speeds and decelerations. The rigid vehicles were limited to a single roll by tethering the vehicles to the deceleration cart. The vehicle's roll rate, roll angle, lateral acceleration and Anthropomorphic Test Devices (ATD) neck responses generated from the rigid SUV were compared to the responses of a full vehicle production SUV under similar test conditions. The rigid SUV and Car devices were then used to examine the effects of activating safety belt pre-tensioning systems and roof mounted side curtain airbags at various times on ATD neck forces and moments.

This paper explores the accuracy of a planar, impulse-momentum impact model in representing the dynamics of three vehicle-to-ground impacts that occurred during a SAE J2114 dolly rollover test. The impacts were analyzed, first, using video analysis techniques to obtain the actual velocity conditions, accelerations, impact force components and the energy loss for each of the impacts. Next, these same impacts were analyzed using the known initial velocity conditions and the subject impact model. The equations of this impact model yielded calculated values for the velocity changes and energy loss for each impact. These calculated results were then compared to the actual dynamics data from the video analysis of the impacts to determine the accuracy of the impact model results. For all three vehicle-to-ground impacts considered in this study, the impact model results for the velocity changes and energy loss showed excellent agreement with the video analysis results for these parameters.

This paper examines the use of camera-matching video analysis techniques to quantify the vehicle dynamics and deformation for a dolly rollover test run in accordance with the SAE Recommended Practice J2114. The method presented enables vehicle motion data and deformation measurements to be obtained without the use of the automated target tracking employed by existing motion tracking systems. Since it does not rely on this automated target tracking, the method can be used to analyze video from rollover tests which were not setup in accordance with the requirements of these automated motion tracking systems. The method also provides a straightforward technique for relating the motion of points on the test vehicle to the motion of the vehicle's center-of-mass. This paper, first, describes the specific rollover test that was utilized. Then, the camera-matching method that was used to obtain the vehicle motion data and deformation measurements is described.

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.

An experimental study was conducted using a dynamic rollover component test system (ROCS) to study the effects of activating a pyro-mechanical buckle pre-tensioner and an electric retractor on the driver and front right passenger head and pelvis excursions. The ROCS is a unique system capable of producing vehicle responses that replicate four distinct phases of a tripped rollover: trip initiation, roll initiation, free-flight vehicle rotation, and vehicle to ground contact. This component test system consists of a rigid occupant compartment derived from a mid-size SUV with complete 1st row seating and interior trim, a simulated vehicle suspension system and an elastic vehicle-to-ground-contact surface. The ROCS system was integrated with a Deceleration Rollover Sled (DRS). Dynamic responses of the ROCS system, including both the rigid compartment and occupant, were measured and recorded.

This paper presents an image analysis of a laboratory-based rollover crash test using camera-matching photogrammetry. The procedures pertaining to setup, analysis and data process used in this method are outlined. Vehicle roll angle and rate calculated using the method are presented and compared to the measured values obtained using a vehicle mounted angular rate sensor. Areas for improvement, accuracy determination, and vehicle kinematics analysis are discussed. This paper concludes that the photogrammetric method presented is a useful tool to extract vehicle roll angle data from test video. However, development of a robust post-processing tool for general application to crash safety analysis requires further exploration.

Full vehicle dynamic crash tests are commonly used in the development of rollover detection sensors, algorithms and occupant protection systems. However, many published studies have utilized component level rollover test fixtures for rollover related occupant kinematics studies and restraint system evaluation and development. A majority of these fixtures attempted to replicate only the rotational motion that occurs during the free flight phase of a typical full vehicle rollover crash test. In this paper, a description of the methods used to design a new dynamic component rollover test device is presented. A brief summary of several existing rollover component test methods is included. The new system described in this paper is capable of replicating the transfer of lateral energy into rotational vehicle motion that is present in many tripped laboratory based rollover crash tests.

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.

A number of studies, using data from NASS-CDS, have shown a large percentage of rollover crashes can be classified as tripped events. In many cases, the requirements for a tripped rollover detection algorithm are driven by the timely activation of an occupant containment device. To meet these requirements rollover detection algorithms have been developed by utilizing vehicle roll rate, lateral and vertical accelerations data collected primarily from laboratory tests. This study identifies and examines several challenges associated with developing a rollover detection algorithm with enhanced capabilities. Enhancement of the detection algorithm is explored by considering additional vehicle responses: forward velocity and sideslip angle. With the additional signals, discrimination of rollover crashes from other crash modes is discussed. Potential field/laboratory test modes are proposed to generate the additional vehicle signals.

Vehicle motion prior to a rollover can influence an occupant's position in the vehicle. Lateral deceleration prior to a tripped rollover may cause the occupant to move outboard. This outboard motion may have several effects on the occupant such as, repositioning the occupant with relation to the seat and seat restraint, and allowing the occupant's head to travel further into the side curtain deployment zone. To reduce occupant lateral motion, the effectiveness of applying tension to the seatbelt was evaluated. The evaluation consisted of two test conditions simulating vehicle lateral motion prior to a trip using a Deceleration Rollover Sled [1]. The test conditions were designed to ensure a vehicle experiences a period of pure lateral motion before the onset of a lateral trip. A standard seat belt combined with various means of applying tension and activated at different times during the test were evaluated.