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

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This paper reports a method for analyzing data from a DriveCam unit to determine impact speeds and velocity changes in vehicle-to-vehicle impacts. A DriveCam unit is an aftermarket, in-vehicle, event-triggered video and data recorder. When the unit senses accelerations over a preset threshold, an event is triggered and the unit records video from two camera views, accelerations along three directions, and the vehicle speed with a GPS sensor. In conducting the research reported in this paper, the authors ran four front-to-rear crash tests with two DriveCam equipped vehicles. For each test, the front of the bullet vehicle impacted the rear of the stationary target vehicle. Each of the test vehicles was impacted in the rear twice-once at a speed of around 10 mph and again at a speed around 25 mph. The accuracy of the DriveCam acceleration data was assessed by comparing it to the data from other in-vehicle instrumentation. We found that, for inline front-to-rear crashes like those tested in this paper, the video, GPS and acceleration data reported by the DriveCam systems is useful for reconstructing crashes, provided that the reconstructionist accounts for potential limitations in the data.

Section: Target Vehicle Analysismentioning

confidence: 99%

Using Data from a DriveCam Event Recorder to Reconstruct a Vehicle-to-Vehicle Impact

Rose¹,

Carter²,

Pentecost³

et al. 2013

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“…The authors have elsewhere reported video analysis of a dolly rollover crash test [27] and analysis of three vehicle-to-ground impacts that occurred during that crash test [26]. In that test, the downward velocity for the three vehicle-to-ground impacts that were analyzed varied between 2.0 and 4.0 mph.…”

Section: Figurementioning

confidence: 99%

“…These impact durations vary between 200 and 500 milliseconds. The authors have elsewhere presented video analysis of another dolly rollover crash test run with a sport utility vehicle on a concrete surface along with analysis of three vehicle-to-ground impacts that occurred during that crash test [26,27]. In that test, the impact durations for the three vehicle-to-ground impacts that were analyzed varied between 165 and 230 milliseconds when obtained with the vehicle accelerations.…”

Section: Impact Durationmentioning

confidence: 99%

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

Rose¹,

Beauchamp²,

Fenton³

2008

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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.

“…In other words, camera matching an object in one image is the same process as camera matching the position of an object over several images, though the result of matching several images is that the change in position can also be determined. Previous literature has developed the technique of tracking video in this manner [5,6,7]. However, to track an object in a video using camera matching photogrammetry, the location of the object must be manually matched at each frame that is being analyzed, which can be time consuming.…”

Section: Introductionmentioning

confidence: 99%

“…Having tracked the position of a pixel in a video, and converted the coordinates to a matrix of x and y values, principles of camera matching photogrammetry are utilized to determine the positon of the camera in three dimensional space. [1,2,7]. This requires creating geometry, from scanning, surveying or other methods, of the scene represented in the video.…”

Section: Introductionmentioning

confidence: 99%

Determining Position and Speed through Pixel Tracking and 2D Coordinate Transformation in a 3D Environment

Neale¹,

Hessel²,

Koch³

2016

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This paper presents a methodology for determining the position and speed of objects such as vehicles, pedestrians, or cyclists that are visible in video footage captured with only one camera. Objects are tracked in the video footage based on the change in pixels that represent the object moving. Commercially available programs such as PFTrack tm and Adobe After Effects tm contain automated pixel tracking features that record the position of the pixel, over time, two dimensionally using the video's resolution as a Cartesian coordinate system. The coordinate data of the pixel over time can then be transformed to three dimensional data by ray tracing the pixel coordinates onto three dimensional geometry of the same scene that is visible in the video footage background. This paper explains the automated process of first tracking pixels in the video footage, and then remapping the 2D coordinates onto three dimensional geometry using previously published projection mapping and photogrammetry techniques. The results of this process are then compared to VBOX recordings of the objects seen in the video to evaluate the accuracy of the method. Some beneficial aspects of this process include the time reduced in tracking the object, since it is automated, and also that the shape and size of the object being tracked does not need to be known since it is a pixel being tracked, rather than the geometry of the object itself. Concept of 2D Coordinate Transformation The tracking of objects in video, also called motion tracking, can be a manual or automated process where, in an x and y coordinate system determined by the video's resolution, a discrete pixel, or series of