Occupant Position Recognition with Seat Surface Pressure Distributions and Support Vector Machines Classifier

Abstract

In the intelligent airbag system, the detection accuracy of occupant position is the precondition and plays a vital role in controlling airbag detonation time and inflation strength during the crash. Through accurately analyzing the seat surface pressure distributions of different occupant sitting position and types, an occupant position recognition algorithm which purely uses occupant pressure distribution information measured by seat pressure sensors is presented with the method of support vector machine. The distribution samples with different occupant sitting positions and types are used to train and test the recognition algorithm, thus verifying its validity and accuracy.