Modeling of occupant's head movement behavior in motion sickness study via time delay neural network. (February 2020)

• Record Type: Journal Article
• Authors: Saruchi, Sarah 'A; Ariff, Mohd HM; Zamzuri, Hairi; Hassan, Nurhaffizah; Wahid, Nurbaiti
• Is Part Of: Simulation. Volume 96:Number 2(2020)
• Page Start: 131
• Page End: 140
• Publication Date: 2020-02
• Subjects: Motion sickness -- time delay neural network -- head roll -- lateral acceleration -- correlation model -- head movement predictor; Computer simulation -- Periodicals; 003.3
• DOI: 10.1177/0037549719862864
• Languages: English
• ISSNs: 0037-5497

Abstract

Passengers are more susceptible to experiencing motion sickness (MS) than drivers. The difference in the severity of MS is due to their different head movement behavior during curve driving. When negotiating a curve, the passengers tilt their heads towards the lateral acceleration direction while the drivers tilt their heads against it. Thus, to reduce the passengers' level of MS, they need to reduce their head's tilting angle towards the lateral acceleration direction. Designing MS minimization strategies is easier if the correlation between the head movement and lateral acceleration is known mathematically. Therefore, this paper proposes the utilization of a time delay neural network (TDNN) to model the correlation of the occupant's head movement and lateral acceleration. An experiment was conducted to gather real-time data for the modeling process. The results show that TDNN manages to model the correlation by producing a similar output response to the actual response. Thus, it is expected that the correlation model could be used as an occupant's head movement predictor tool in future studies of MS.