Stephen J. Fenton

Using Digital Photogrammetry to Determine Vehicle Crush and Equivalent Barrier Speed (EBS)

This paper presents a method of determining a vehicle crush and equivalent barrier speed (EBS) using digital photogrammetry. A state-of-the-art documentation technique called close-range photogrammetry allows engineers and accident reconstructionists to create three-dimensional (3-D) computer models of damaged vehicles utilizing photographs. Utilizing photogrammetric software, engineers can digitize accident scene photographs to create accurate 3-D computer models of the vehicles, which can be used to quantify structural damage sustained by the vehicles. Crush deformation can be quantified utilizing this process, and the resulting crush dimensions can be input into engineering software to determine a vehicles EBS. (A) For the covering abstract of the conference see IRRD E201455.

An Examination of the CRASH3 Effective Mass Concept

This paper examines the validity of the effective mass concept used in the CRASH 3 damage analysis equations. In this study, the effective mass concept is described, the simplifying assumptions that it entails are detailed, and the accuracy of the concept is tested by comparing ∆Vs calculated from the CRASH 3 equations to results of numerical simulations with a non-central impact model. This non-central impact model allowed the effective mass concept to be tested in isolation from other assumptions of the CRASH 3 program. The results of this research have shown that the effective mass concept accurately models the effects of collision force offset when certain conditions are met. These conditions are discussed, along with their implications for damage interpretation. This paper also presents an analytic expression that relates damage energy to closing speed (initial relative velocity) for the general case of non-central collisions. Equations relating damage energy to closing speed for the case of central collisions have been discussed extensively in the literature. However, a comparable equation for the general case of vehicle-to-vehicle noncentral impacts has not been reported. The effective mass concept is used to generalize the relationship between closing speed and damage energy.

Determining Vehicle Steering and Braking from Yaw Mark Striations

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.

Image Analysis of Rollover Crash Tests Using Photogrammetry

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.

Restitution Modeling for Crush Analysis: Theory and Validation

This paper describes, demonstrates and validates a method for incorporating the effects of restitution into crush analysis. The paper first defines the impact coefficient of restitution in a manner consistent with the assumptions of crush analysis. Second, modified equations of crush analysis are presented that incorporate this coefficient of restitution. Next, the paper develops equations that model restitution response on a vehicle-specific basis. These equations utilize physically meaningful empirical constants and thus improve on restitution modeling equations already in the literature of accident reconstruction. Finally, the paper presents analysis of four vehicle-to-vehicle crash tests, demonstrating that the application of the restitution model derived in this paper results in crush analysis yielding more accurate ΔV calculations.

A Method to Quantify Vehicle Dynamics and Deformation for Vehicle Rollover Tests Using Camera-Matching Video Analysis

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. Finally, the data obtained from the video analysis is analyzed and compared to data obtained from on-board instrumentation. Ultimately, the camera-matching technique is shown to be a viable technique for obtaining three-dimensional vehicle motion during a rollover crash test. As a means of obtaining vehicle deformation, the technique will need further development. INTRODUCTION This paper examines the use of a camera-matching photogrammetric technique to track the motion and dynamic deformation of a vehicle during a SAE J2114 dolly rollover test. The methodology presented enables vehicle motion data and deformation measurements to be obtained without the use of the automated target tracking employed by 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 such 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. In 2006, Chou, et al. (2006), reported video analysis results for a 500 millisecond segment of another dolly rollover test [1]. In this earlier research, the authors primarily examined the effectiveness of the technique for obtaining roll angles and roll velocities from the test. The analysis reported by Chou, et al., was limited because the characteristics and locations of the cameras that recorded the crash test were unknown, as was the exact geometry of the crash test facility and the crash test vehicle. 2008-01-0350 A Method to Quantify Vehicle Dynamics and Deformation for Vehicle Rollover Tests Using Camera-Matching Video Analysis Nathan A. Rose, William T.C. Neale, Stephen J. Fenton and David Hessel

Integrating Monte Carlo Simulation, Momentum- Based Impact Modeling, and Restitution Data to Analyze Crash Severity

Crash severity is quantified by the change in velocity experienced by a vehicle during an impact along with the time duration over which that change in velocity occurs. Since the values of the input parameters for calculating the change in velocity are not known exactly, there is uncertainty associated with the calculated change in velocity. Accurate evaluation of the crash severity will, therefore, include analysis of the effect that uncertainties in the values of the input parameters have on the calculated change in velocity. Monte Carlo simulation, a statistical technique, enables the reconstructionist to evaluate the effect of uncertainty on the analysis of crash severity. Use of the Monte Carlo simulation technique is beneficial since a reconstructionist can enter a range of values for each input parameter. A probability distribution can be assigned to the range of values, which indicates the likelihood that any value in that range corresponds to the actual value of the parameter. The simulation generates thousands of possible combinations of the input parameters selected from the specified ranges, monitors the results of the combinations and analyzes them statistically. Application of the Monte Carlo technique is intended to improve the legitimacy of crash severity analysis by helping the reconstructionist consider a wide range of possible solutions within the bounds of the imperfect data and report statistically meaningful ranges for the change in velocity. This paper demonstrates the application of the Monte Carlo technique to impact severity analysis using a derived two-dimensional, rigid body, momentum-based impact model. Thorough guidance is given to aid the reconstructionist in integrating the momentum model with the Monte Carlo simulation technique and this method is illustrated with a case study. Since the impact model employs restitution constraints in the normal and tangential directions, the effect of uncertainty in formulating appropriate ranges for the values of the restitution coefficients is discussed. NOTATION m mass I moment of inertia V velocity

Analysis of Vehicle-to-Ground Impacts During a Rollover with an Impulse-Momentum Impact Model

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 using video analysis techniques in order 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. These results suggest that it is reasonable to use this impact model to examine the influence of various factors on rollover dynamics.

Determining Crash Data Using Camera Matching Photogrammetric Technique

Accident scene photographs contain important information that can be useful in determining how accidents happened. However, dimensions are difficult to gather from photographs. The size of an object in the photographs depends on how far away from the camera the object is located. An object in the background looks smaller and will measure smaller than the same size object in the foreground. This phenomenon is called perspective distortion. Photogrammetry was introduced in the late 1800’s as a tool to compensate for the perspective distortion and assist in gathering dimensions from photographs. One of the early techniques was to create a transparent miniature of a photograph and place the miniature in the view screen on the camera. The camera was then taken to the scene and matched to the correct position such that the image in the scene matched the image in the view screen. Today, using computer modeling software, a scene can be created in the computer model that matches the actual photograph. Using a technique called camera matching, the camera in the computer can be adjusted to match the photograph. Once properly matched, dimensions within the photograph can be gathered. This technique is useful in gathering dimensional data from crash scene photographs like the point of impact and the point of rest of crash vehicles. Once the crash scene dimensions are determined, the accident can be reconstructed using the principals of conservation of momentum and energy.

The Influence of Vehicle-to-Ground Impact Conditions on Rollover Dynamics and Severity

This paper explores the influence of the impact conditions on the dynamics and the severity of rollover crashes. It describes how 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 vehicles 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 are used to give the parameter study an empirical basis.