Data Acquisition and Processing for the Optimization of an Algorithm for Vehicle Safety Objective Rating Metrics and Injury Severity Prediction
Open Access
Article
Conference Proceedings
Authors: Katelyn Williams, Steven Jiang, Devon Albert
Abstract: evaluation and the most common ORM is CORA (Correlation and Analysis). Currently, no standards exist for the evaluation of CORA: it is up to the researcher to determine whether or not to use its software (CORAPlus) and what parameters they deem important for analysis. This high level of subjectivity shows there is a need for a more streamlined approach for the data processing of the CORA ORM. The goal of this research is to develop a systematic approach for future researchers to process and analyze the CORA ORM consistently. Data acquisition and preprocessing are an important part of this process. This paper describes how data can be extracted from the NHTSA Biomechanics Database which is comprised of over 15,000 biomechanical tests in an online repository, and how data can be filtered and processed to generate matched time histories for ORM processing. This proposed approach of data processing and optimization is the basis for the development of an algorithm that correlates objective rating metric similarity scores and injury severity. It has the potential to contribute to the improvement of vehicle safety.
Keywords: Objective Rating Metrics, Data Optimization, Data Processing
DOI: 10.54941/ahfe1005779
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