title: Integration of Active and Passive Safety Technologies--A Method to Study and Estimate Field Capability.
abstract: The objective of this study is to develop a method that uses a combination of field data analysis, naturalistic driving data analysis, and computational simulations to explore the potential injury reduction capabilities of integrating passive and active safety systems in frontal impact conditions. For the purposes of this study, the active safety system is actually a driver assist (DA) feature that has the potential to reduce delta-V prior to a crash, in frontal or other crash scenarios. A field data analysis was first conducted to estimate the delta-V distribution change based on an assumption of 20% crash avoidance resulting from a pre-crash braking DA feature. Analysis of changes in driver head location during 470 hard braking events in a naturalistic driving study found that drivers' head positions were mostly in the center position before the braking onset, while the percentage of time drivers leaning forward or backward increased significantly after the braking onset. Parametric studies with a total of 4800 MADYMO simulations showed that both delta-V and occupant pre-crash posture had pronounced effects on occupant injury risks and on the optimal restraint designs. By combining the results for the delta-V and head position distribution changes, a weighted average of injury risk reduction of 17% and 48% was predicted by the 50th percentile Anthropomorphic Test Device (ATD) model and human body model, respectively, with the assumption that the restraint system can adapt to the specific delta-V and pre-crash posture. This study demonstrated the potential for further reducing occupant injury risk in frontal crashes by the integration of a passive safety system with a DA feature. Future analyses considering more vehicle models, various crash conditions, and variations of occupant characteristics, such as age, gender, weight, and height, are necessary to further investigate the potential capability of integrating passive and DA or active safety systems.
authors.affiliation: University of Michigan Transportation Research Institute.
authors.forename: Jingwen
authors.initials: J
authors.lastname: Hu
authors.affiliation: University of Michigan Transportation Research Institute.
authors.forename: Carol A
authors.initials: CA
authors.lastname: Flannagan
authors.affiliation: University of Michigan Transportation Research Institute.
authors.forename: Shan
authors.initials: S
authors.lastname: Bao
authors.affiliation: Ford Motor Company.
authors.forename: Robert W
authors.initials: RW
authors.lastname: McCoy
authors.affiliation: Ford Motor Company.
authors.forename: Kevin M
authors.initials: KM
authors.lastname: Siasoco
authors.affiliation: Ford Motor Company.
authors.forename: Saeed
authors.initials: S
authors.lastname: Barbat
mesh_terms: D000063:Accidents, Traffic / Q000517:prevention & control*; D000328:Adult; D000368:Aged; D001336:Automobiles; D003198:Computer Simulation; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D018986:Motor Vehicles; D012449:Safety; D014947:Wounds and Injuries / Q000517:prevention & control*; D055815:Young Adult