ANN driver model based on seat to head transmissibility

Abstract

Protection and prevention of vehicle driver health and working capabilities are the most important task in vehicle design phase. In order to improve and accelerate vehicle design process, different driver models have been developed in last few decades. Models development depends on computer and software improvement. Wide application of artificial neural network (ANN) and deep learning methods caused its application in human body models exposed to wide variety of vibration. In this paper, model of vehicles driver exposed to vertical random vibration is developed based on ANN. Different network structures and activation functions were analyzed in order to obtain optimal network structure in frequency domain. Input data were seat to head transmissibility frequency response function of human body exposed to vertical random vibration obtained in laboratory experiment. Validation of adopted model showed good correlation with experimental data. Amount of transmitted vibration through vehicle drivers body can be predicted by application of proposed model.