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This paper explores the influence of the impact conditions on the dynamics and the severity of rollover crashes. Causal connections are sought between the impact conditions and the crash attributes to which they lead. The paper begins by extending previously presented equations that describe the dynamics of an idealized vehicle-to-ground impact. It then considers the behavior of these equations under a variety of impact conditions that occur during real-world rollovers. Specifically, the equations of this impact model are used to explore the ways in which and the extent to which rollover dynamics and severity are influenced by the following factors: (1) the vehicle's shape and its orientation at impact, (2) its weight, center-of-mass location, and roll moment of inertia, (3) its translational speed, (4) its downward velocity, and (5) its roll velocity. Throughout this discussion, data from real-world and staged rollover crashes is used to give the parameter study an empirical basis.

This paper explores the dynamics of rollover crashes and examines factors that influence the severity of the roof-to-ground impacts that occur during these crashes. The paper first reports analysis of 12 real-world rollover accidents that were captured on video. Roll rate time histories for the vehicles in these accidents are reported and the characteristics of these curves are analyzed. Next, the paper uses analytical modeling to explore the influence that the trip phase characteristics may have on the severity of roof-to-ground impacts that occur during the roll phase. Finally, the principle of impulse and momentum is used to derive an analytical impact model for examining the mechanics of a roof-to-ground impact. This modeling is used to identify the influence of various impact conditions on the severity of a roof-to-ground impact.

This paper presents event data from the Sensing and Diagnostic Module (SDM) of a 2004 Chevrolet Malibu during high speed yaw testing. Yaw tests were performed using tires that were intact and tires that had the tread removed. The tires that had the tread removed were placed at various wheel positions on the vehicle (e.g. leading side - front, leading side -rear, trailing side - rear). This testing simulates the loss of control phase subsequent to a tread separation. Speeds up to 117 km/h (72.9 mph) were achieved. A simple electro-mechanical device was incorporated to the dynamic testing to simulate a low-severity non-deployment event that triggered the recording of pre-crash data by the SDM. The SDM data from the tests was imaged and compared to reference data from vehicle-mounted instrumentation recording wheel speed, steering angle, measured vehicle sideslip angle and GPS calculated over the ground speed.

This paper presents equations that relate the orientation and spacing of yaw mark striations to the vehicle braking and steering levels present at the time the striations were deposited. These equations, thus, provide a link between physical evidence deposited on a roadway during a crash (the tire mark striations) and actions taken by the driver during that crash (steering and braking inputs). This paper also presents physical yaw tests during which striated yaw marks were deposited. Analysis of these tests is conducted to address the degree to which the presented equations can be used to determine a driver’s actual steering and braking inputs. As a result of this testing and analysis, it was concluded that striated tire marks can offer a meaningful glimpse into the steering and braking behavior of the driver of a yawing vehicle. It was also found that consideration of yaw striations allows for the reconstruction of a vehicle’s post-impact yaw motion from a single tire mark.

This paper evaluates the use of PC-Crash simulation software for modeling the dynamics of a dolly rollover crash test. The specific test used for this research utilized a Ford sport utility vehicle and was run in accordance with SAE J2114. Scratches, gouges, tire marks and paint deposited on the test surface by the test vehicle were documented photographically and by digital survey and a diagram containing the layout of these items was created. The authors reviewed the test video to determine which part of the vehicle deposited each of these pieces of evidence. Position and orientation data for the vehicle in the test were then obtained using video analysis techniques. This data was then analyzed to determine the vehicle’s translational and rotational velocities throughout the test. Next, the test was modeled using PC-Crash.

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.