Video Analysis and Analytical Modeling of Actual Vehicle/Pedestrian Collisions 2014-01-0483
Numerous mathematical models for reconstructing vehicle-pedestrian collisions have been developed over the years utilizing common sources of physical evidence. As sources of video data recording proliferate, new sources of physical evidence are now available in some cases. This paper presents an expanded methodology for analyzing video footage of actual pedestrian collisions, including both static and dynamic camera positions. Each video was analyzed using digitizing motion analysis software to quantify the pre-impact and post-impact trajectories and speeds of the vehicle, the pedestrian, and the camera position for each collision.
The relationship between vehicle speed and pedestrian throw distance has frequently been used in collision reconstruction to answer questions regarding vehicle/pedestrian impacts. Several approaches to reconstructing vehicle/pedestrian collisions have been developed and published in the literature using equations derived from empirical models, principles of mechanics, or hybrid approaches. The empirical and hybrid categories of equations are based primarily on statistical analysis of staged crash tests with cadavers and dummies, or computer modeling simulations. Some prior studies have discussed vehicle/pedestrian reconstruction equations derived from staged tests or simulations and compared them to a small set of real-world event data. New data from actual video-captured vehicle-pedestrian collisions are presented as a comparison data set for further validation of previously published empirical and hybrid pedestrian reconstruction methodologies.
Citation: Rush, T., Przybyla, J., Melcher, D., and Sax, C., "Video Analysis and Analytical Modeling of Actual Vehicle/Pedestrian Collisions," SAE Technical Paper 2014-01-0483, 2014, https://doi.org/10.4271/2014-01-0483. Download Citation
Author(s):
Thomas Rush, Jay Przybyla, Daniel Melcher, Christian Sax
Affiliated:
Armstrong Forensic Engineers Inc.
Pages: 14
Event:
SAE 2014 World Congress & Exhibition
ISSN:
0148-7191
e-ISSN:
2688-3627
Related Topics:
Mathematical models
Computer simulation
Impact tests
Statistical analysis
Simulation and modeling
Anthropometric test devices
Computer software and hardware
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