With on-site data annotation and reduction labs and extensive analysis experience, the institute realized the role it could play in helping others mine and reduce VTTI data to answer research questions about driver behavior and performance.
VTTI data reduction laboratories process the raw data collected in VTTI studies and reduce it into a format that allows specific research questions to be accurately and effectively answered.
Data reductionists undergo a rigorous training and evaluation process before they are approved to reduce data for projects. Additionally, each reductionist's data are periodically spot-checked by the data supervisor to ensure that quality standards are maintained. For all studies, a series of testing protocols is in place to ensure that data reduction is consistent both between reductionists and from a single reductionist over time. These tests are conducted on a regular basis to ensure that there is no drift in the quality of reduced data.
VTTI has developed software tools to significantly reduce the time required to analyze eyeglance and other video-based data. These software tools allow the data reductionists to examine the data and insert additional information such as eyeglance locations and lengths; driving environment; and near-crash or crash factors. The videos are also synched with kinematic data to allow detailed crash and near-crash analyses.