Vehicle occupant classification algorithm based on T-S fuzzy model

One of the critical logic deployment challenges faced by intelligent airbag system is whether the system can accurately determine the type of the occupant sitting in different postures. The main objective of this paper is the application of seat pressure sensors to predict the occupant classification, such as 5th percentile adult female and 50th percentile adult male and 95th percentile adult male. In the experiments, the occupants are recruited to sit in specified postures. During sitting, the pressure data of the occupants are measured. After that, T-S fuzzy model is introduced to investigate the highly nonlinear relationship between the pressure and the weight of the occupant. Finally, the system uses the weight information to determine the type of the occupant. Since the good validity and accuracy of the weight calculated by the T-S fuzzy model are shown in the experiments, the proposed algorithm can effectively identify the type of the occupant.