1. Methodology for vehicle safety development and assessment accounting for occupant response variability to human and non-human factors
- Author
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Jeffrey Richard Crandall, Jason Forman, Samuel H. Huddleston, and Daniel Perez-Rapela
- Subjects
Computer science ,0206 medical engineering ,Monte Carlo method ,Biomedical Engineering ,Bioengineering ,02 engineering and technology ,03 medical and health sciences ,0302 clinical medicine ,Vehicle safety ,Craniocerebral Trauma ,Humans ,Computer Simulation ,Probability ,Anthropometry ,030229 sport sciences ,General Medicine ,Middle Aged ,020601 biomedical engineering ,Response Variability ,Biomechanical Phenomena ,Computer Science Applications ,Reliability engineering ,Test (assessment) ,Human-Computer Interaction ,Motor Vehicles ,Neural Networks, Computer ,Current (fluid) ,Head ,Algorithms - Abstract
The use of standardized anthropomorphic test devices and test conditions prevent current vehicle development and safety assessments from capturing the breadth of variability inherent in real-world occupant responses. This study introduces a methodology that overcomes these limitations by enabling the assessment of occupant response while accounting for sources of human- and non-human-related variability. Although the methodology is generic in nature, this study explores the methodology in its application to human response in far-side motor vehicle crashes as an example. A total of 405 human body model simulations were conducted in a mid-sized sedan vehicle environment to iteratively train two neural networks to predict occupant head excursion and thoracic injury as a function of occupant anthropometry, impact direction and restraint configuration. The neural networks were utilized in Monte Carlo simulations to calculate the probability of head-to-intruding-door impacts and thoracic AIS 3+ as a function of the restraint configuration. This analysis indicated that the vehicle used in this study would lead to a range of 667 to 2,448 head-to-intruding-door impacts and a range of 3,041 to 3,857 cases of thoracic AIS 3+ in the real world, depending on the seatbelt load limiter. These real-world results were later successfully validated using United States field data. This far-side assessment illustrates how the methodology incorporates the human and non-human variability, generates response surfaces that characterize the effects of the variability, and ultimately permits vehicle design considerations and injury predictions appropriate for real-world field conditions.
- Published
- 2020
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