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Greenwood Village, CO, United States

Rose N.A.,Kineticorp LLC | Carter N.,Kineticorp LLC
SAE Technical Papers

In a 2012 paper, Brach, Brach, and Louderback (BBL) investigated the uncertainty that arises in calculating the change in velocity and crush energy with the use of the CRASH3 equations (2012-01-0608). They concluded that the uncertainty in these values caused by variations in the stiffness coefficients significantly outweighed the uncertainty caused by variations in the crush measurements. This paper presents a revised analysis of the data that BBL analyzed and further assesses the level of uncertainty that arises in CRASH3 calculations. While the findings of this study do not invalidate BBL's ultimate conclusion, the methodology utilized in this paper incorporated two changes to BBL's methodology. First, in analyzing the crash test data for several vehicles, a systematic error that is sometimes present in the reported crush measurements was accounted for and corrected. This systematic error arises when a vehicle's plastic bumper fascia rebounds more than the underlying structure, creating an air gap and causing the reported crush measurements both to underestimate the actual deformation and to exhibit more scatter than they otherwise would. This scatter translates into uncertainty in the stiffness coefficients. Second, linear regression was used to obtain the stiffness coefficients and to quantify their uncertainty. Instead of using linear regression, BBL assumed the same damage onset speed (b0) for each crash test. In essence, this means that BBL assumed a value for one of the stiffness coefficients, with the only variability in that coefficient coming from the differences in vehicle weights from test to test. The methodology employed in this paper eliminated the need to assume a damage onset speed. Copyright © 2014 SAE International. Source

Neale W.T.,Kineticorp LLC | Hessel D.,Kineticorp LLC | Terpstra T.,Kineticorp LLC
SAE Technical Papers

All camera lenses contain optical aberrations as a result of the design and manufacturing processes. Lens aberrations cause distortion of the resulting image captured on film or a sensor. This distortion is inherent in all lenses because of the shape required to project the image onto film or a sensor, the materials that make up the lens, and the configuration of lenses to achieve varying focal lengths and other photographic effects. The distortion associated with lenses can cause errors to be introduced when photogrammetric techniques are used to analyze photographs of accidents scenes to determine position, scale, length and other characteristics of evidence in a photograph. This paper evaluates how lens distortion can affect images, and how photogrammetrically measuring a distorted image can result in measurement errors. Lens distortion from a variety of cameras is analyzed, and the ultimate effect that this distortion has on the image is evaluated, with a discussion on the overall difference this distortion would cause to measuring evidence in an image, such as tire mark distances and curvature. Ways of correcting this distortion are also addressed. Copyright © 2011 SAE International. Source

Rose N.A.,Kineticorp LLC | Carter N.,Kineticorp LLC | Pentecost D.,Kineticorp LLC
SAE Technical Papers

PC-Crash™, a widely used crash analysis software package, incorporates the capability for modeling non-constant vehicle acceleration, where the acceleration rate varies with speed, weight, engine power, the degree of throttle application, and the roadway slope. The research reported here offers a validation of this capability, demonstrating that PC-Crash can be used to realistically model the build-up of a vehicle's speed under maximal acceleration. In the research reported here, PC-Crash 9.0 was used to model the full-throttle acceleration capabilities of three vehicles with automatic transmissions-a 2006 Ford Crown Victoria Police Interceptor (CVPI), a 2000 Cadillac DeVille DTS, and a 2003 Ford F150. For each vehicle, geometric dimensions, inertial properties, and engine/drivetrain parameters were obtained from a combination of manufacturer specifications, calculations, inspections of exemplar vehicles and full-scale vehicle testing. In each case, the full-throttle acceleration of the vehicles modeled in PC-Crash showed good agreement with the acceleration of the real vehicles in our road tests. Copyright © 2014 SAE International. Source

Rose N.A.,Kineticorp LLC | Carter N.,Kineticorp LLC | Beauchamp G.,Kineticorp LLC
SAE Technical Papers

Calculating the speed of a yawing and braked vehicle often requires an estimate of the vehicle deceleration. During a steering induced yaw, the rotational velocity of the vehicle will typically be small enough that it will not make up a significant portion of the vehicle's energy. However, when a yaw is impact induced and the resulting yaw velocity is high, the rotational component of the vehicle's kinetic energy can be significant relative to the translational component. In such cases, the rotational velocity can have a meaningful effect on the deceleration, since there is additional energy that needs dissipated and since the vehicle tires can travel a substantially different distance than the vehicle center of gravity. In addition to the effects of rotational energy on the deceleration, high yaw velocities can also cause steering angles to develop at the front tires. This too can affect the deceleration since it will influence the slip angles at the front tires. This paper explores the influence of high rotational energies and impact induced steering on the deceleration experienced by a vehicle following an impact. © 2016 SAE International. Source

Neale W.T.,Kineticorp LLC | Marr J.,Kineticorp LLC | Hessel D.,Kineticorp LLC
SAE Technical Papers

This paper presents a methodology for generating photo realistic computer simulation environments of nighttime driving scenarios by combining nighttime photography and videography with video tracking [1] and projection mapping [2] technologies. Nighttime driving environments contain complex lighting conditions such as forward and signal lighting systems of vehicles, street lighting, and retro reflective markers and signage. The high dynamic range of nighttime lighting conditions make modeling of these systems difficult to render realistically through computer generated techniques alone. Photography and video, especially when using high dynamic range imaging, can produce realistic representations of the lighting environments. But because the video is only two dimensional, and lacks the flexibility of a three dimensional computer generated environment, the scenarios that can be represented are limited to the specific scenario recorded with video. However, by combining the realistic imagery from video and photographs with the flexibility of a computer generated environment, it is possible to vary any number of factors such as the speed of vehicles and the driver lane position, and to vary the types of vehicles and lighting conditions involved in the scenario. The combination of projection mapping, video tracking, and nighttime video and photography methodologies allow this flexibility. In addition to presenting the methodology and the resulting computer simulation environment, the final simulation is compared to actual video recordings of the same driving scenario to evaluate how similar they are in value, tone, color and visibility. © 2016 SAE International. Source

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