Abstract: Impending rollover events are detected based on vehicle roll rate, roll angle and lateral acceleration, and an assessment of the relative polarities of vehicle roll rate and lateral acceleration. When the vehicle roll rate and lateral acceleration are opposite in polarity, the roll rate vs. roll angle thresholds used to distinguish between rollover events and non-rollover events are more sensitive than for conditions for which the vehicle roll rate and lateral acceleration are of the same polarity. Additionally, the roll rate vs. roll angle thresholds are adaptively modified based on roll angle and lateral acceleration to provide increased detection sensitivity under conditions that typically precede a rollover event, and reduced detection sensitivity under conditions for which a rollover event is unlikely.

Abstract: An event discrimination methodology executes multiple versions of the same or different event discrimination algorithms and logically or arithmetically combines their outputs to distinguish between specified events and non-events. One given algorithm is repeatedly executed with different sets of calibration data, or alternately, a number of different algorithms are executed. In cases where the algorithm results are arithmetically combined, the weights accorded to each algorithm result are dynamically adjusted based on driver input or vehicle dynamic behavior data to accord highest weight to the algorithm(s) calibrated to identify events associated with the detected driver input or vehicle dynamic behavior.