Pre-braking behaviors analysis based on Hilbert–Huang transform

Abstract Previous studies have shown that about 90% of traffic accidents are due to human error, which means factors may affect a driver's braking behaviors and thus their driving safety, especially when the driver makes motion. However, most mounted sensors on brake pad, ignoring some extent an analysis behavior before pad is pressed (pre-braking). Therefore, determine effect different drivers' pre-braking behaviors, this study focused analyzing local joints (knee, ankle, toe) by motion capture device. A Hilbert – Huang Transform (HHT)-based body movement method was used decompose realistic complex actions into sub-actions such as intrinsic mode functions (IMF1, IMF2, etc.). Analysis results showed IMF1 common necessary action for all drivers, IMF2 be safety assurance allows right-foot transverse at beginning part process. We also found experienced, male, Phys.50 groups consistent characteristics in HHT scheme, could mean drivers would better performance efficiency during The will useful decomposing discerning specific lead accidents, providing insights training novice guiding construction daily automated assistance or accident prevention systems (advanced systems, ADASs).