The Contribution of Vehicle, Occupant and Crash Factors to the Risk of Injury as a Result of Vehicle Rollover - New approaches to data and modeling analysis
Doktorsavhandling, 2017
crash fatalities in the United States. While more new vehicles are becoming equipped with electronic
stability control and rollover ejection countermeasures as well as increased roof strength, it will take
several years of production before these newer vehicles permeate the fleet and the effectiveness of these
technologies can be fully assessed. In the interim, continued vigilance on assessment of rollover injury
causation is recommended. This can be done through systematic analysis of aggregate field crash data and
specific case studies. Also, mathematical modeling studies can be done to assess the contributions of
vehicle, occupant and crash factors to the injury risk of rollover involved occupants.
The major aims of the research in this thesis are to determine how rollover crash investigations and
crash field data analysis can determine the most frequent types of injuries and their mechanisms that occur
to belted, unejected occupants involved in rollover crashes and, once determined, identify the role of
vehicle, occupant and crash factors that can predict injury risk. The first aim can be achieved through case
studies and aggregate national crash data analysis while the second aim uses finite element and multi-body
modeling of rollover crashes.
Aggregate rollover field data was taken from the National Automotive Sampling System –
Crashworthiness Data System (NASS-CDS). Head, spine (cervical) and thoracic injuries dominated the
injury with specific injury types in each body region indicating areas of further interest to investigate
regarding injury causation. Analysis of specific case studies taken from the Crash Injury Research
Engineering Network (CIREN) indicated that single event, single vehicle (pure) rollovers were associated
with complex mechanisms of cervical spine injuries that were associated with vehicle roof strength
(strength to weight ratio), and the amount of vertical as well as lateral intrusion at the injured occupant
location. Occupant body mass index was a possible contributor to injury risk.
A finite element model of a contemporary sedan was used in a simulation of a Controlled Rollover
Impact System (CRIS) test to identify vehicle and crash parameters that were most associated with high
cervical neck forces in the Hybrid III dummy occupant model. The variables that contributed the most to
the occupant and vehicle structural response were pitch angle, roll angle, and drop height. These factors
determine where and with what force the vehicle roof impacts the ground. The analysis showed that proper
selection of a crash dummy model is also a critical step in the interpretation of effects of the factors used
in analysis. Subsequent MADYMO modeling of the CRIS test with the models of the Hybrid III and
THOR advanced frontal crash dummy and a facet model of the human body were performed with
imported finite element nodal vehicle model outputs representing vehicles with the strongest and weakest
roof. When coupled with a parameter analysis of advanced vehicle seat belt restraints, the analysis showed
that stronger roofs will reduce injury risk, and that restraint systems can provide additional protection to
reduce the potential for occupant head impact to the roof.
The analysis approach to both data and modeling in this thesis provided results through innovative
combined crash field data analysis, parametric computer modeling methods and statistical and human
body modeling techniques to arrive at the conclusions reached. As future vehicle design evolves with
respect to automation and other propulsion systems, designers and engineers need to be aware of the
iv
structural and occupant restraint requirements these vehicles will need as they interact with the fleet and
are exposed to potential rollover situations.
Global Sensitivity Analysis
Roof Inversions
CIREN
Injury Causation
Restraints
Rollover
THOR
Intrusion
CRIS
NASS-CDS
Kinematics
Författare
Stephen Ridella
Chalmers tekniska högskola, Institutionen för tillämpad mekanik, Avdelningen för fordonssäkerhet
National Highway Traffic Safety Administration
Chalmers, Vehicle and Traffic Safety Centre at Chalmers (SAFER)
Styrkeområden
Transport
Ämneskategorier
Transportteknik och logistik
Farkostteknik
Sannolikhetsteori och statistik
ISBN
978-91-7597-574-0
Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 4255
Utgivare
Chalmers
Lindholmen Campus, Forskningsgången 4, Building: Svea , Room: Delta
Opponent: Professor Pete Thomas, Loughborough University