A Strategy to Partition Crash Data to Define Active-Safety Sensors and Product Solutions 2008-21-0032
Both Crash-Avoidance and Pre-Crash active safety technologies are being developed to help reduce the number of crashes and minimize the severity of crashes. The root basis in the development of new and improved active safety technologies always begins with gaining further knowledge about crash kinds and causes.
The dynamics of crashes are quite complex. The evolving precursor crash situation initiated in the Crash-Avoidance time-period will vary from the imminent crash situation in the Pre-Crash time-period. As such, in order to develop the appropriate requirements for both crash-avoidance and pre-crash technologies, they must be analyzed from their respective crash data.
A data-driven methodology process has been developed which partitions the field data with a perspective to crash-avoidance and pre-crash. To support this methodology, a unique set of limited number of “fundamental” crash categories will be defined, in which the field data can be sorted to quantify the respective crash frequency rates and associated crash conditions.
The field data will be used as a basis to identify the appropriate active safety product features and formulate the baseline performance specifications.