The combination of airbag and seatbelt is considered to be the most effective vehicle safety system. However, despite the widespread availability of airbags and a belt use rate of over 85% U.S. drivers involved in crashes continue to be at risk of serious thoracic injury. One hypothesis is that this risk may be due to the lack of airbag deployment or the airbag \'bottoming-out\' in some cases, causing drivers to make contact with the steering. The objective of this study is to determine the influence of various advanced airbags on occupant injury risk in frontal automobile crash. The analysis is based upon cases extracted from the National Automotive Sampling System Crashworthiness Data System (NASS/CDS) database for case years 1993-2011. The approach was to compare the frontal crash performance of advanced airbags against depowered airbags, first generation airbags, and vehicles with no airbag equipped. NASS/CDS steering wheel deformation measurements were used to identify cases in which thoracic injuries may have been caused due to steering wheel impact and deformation. The distributions of injuries for all cases were determined by body region and injury severity. These distributions were used to compare and contrast injury outcomes for cases with frontal airbag deployment for both belted and unbelted drivers. Among frontal crash cases with belted drivers, observable steering wheel deformation occurred in less than 4% of all cases, but accounted for 29% of all serious-to-fatally injured belted drivers and 28% of belted drivers with serious thoracic injuries (AIS3+). Similarly, observable steering wheel deformation occurred in approximately 13% of all cases with unbelted drivers involved in frontal crashes, but accounted for 58% of serious-to-fatally injured unbelted drivers and 66% of unbelted drivers with serious thoracic injuries. In a frontal crash, the factors which were statistically significant in the probability of steering wheel deformation were: longitudinal delta-V, driver weight, and driver belt status. Seatbelt pre-tensioner and load limiters were not significant factors in influencing steering wheel deformation. Furthermore, belted drivers in vehicles with no airbag equipped were found to have 3 times higher odds of deforming the steering wheel, as compared to driver in similar crash scenario. Similarly, unbelted drivers were found to have 2 times greater odds of deforming the steering wheel in vehicles with no airbags equipped as compared to vehicles with advanced airbag. The result also showed no statistically significant difference in the odds of deforming the steering wheel between depowered and advanced airbag. After controlling for crash severity, and driver weight, the study showed that crashes with steering wheel deformation results in greater odds of injury in almost all body regions for both belted and unbelted drivers. Moreover, steering wheel deformation is more likely to occur in unbelted drivers than belted drivers, as well as higher severity crashes and with heavier drivers. Another potential factor in influencing driver crash injury is the knee airbag. After comparing the odds of injury between vehicles with and without knee airbags equipped, belted drivers in vehicles equipped with knee airbag were found to have statistically smaller odds of injury in the thorax, abdomen, and upper extremity. Similarly, the findings showed that unbelted drivers benefited from knee airbag through statistically significant lower odds of chest and lower extremity injuries. However, the results should be considered with caution as the study is limited by its small sample of vehicles with knee airbags. / Master of Science

Arterial roads constitute the majority of the centerline miles of the Florida State Highway System. Severe injury involvements on these roads account for a quarter of the total severe injuries reported statewide. This research focuses on driver injury severity analysis of statewide multilane high speed arterials using crash data for the years 2002 to 2004. The first goal is to test different ways of analyzing crash data (by road entity and crash types) and find the best method of driver injury severity analysis. A second goal is to find driver, vehicle, road and environment related factors that contribute to severe involvements on multilane arterials. Exploratory analysis using one year of crash data (2004) using binary logit regression was used to measure the risk of driver severe injury given that a crash occurs. A preliminary list of significant factors was obtained. A massive data preparation effort was undertaken and a random sample of multivehicle crashes was selected for final analysis. The final injury severity analysis consisted of six road entity models and twenty crash type models. The data preparation and sampling was successful in allowing a robust dataset. The overall model was a good candidate for the analysis of driver injury severity on multilane high speed roads. Driver injury severity resulting from angle and left turn crashes were best modeled by separate non-signalized intersection crash analysis. Injury severity from rear end and fixed object crashes was best modeled by combined analysis of pure segment and non-signalized intersection crashes. The most important contributing factors found in the overall analysis included driver related variables such as age, gender, seat belt use, at-fault driver, physical defects and speeding. Crash and vehicle related contributing factors included driver ejection, collision type (harmful event), contributing cause, type of vehicle and off roadway crash. Multivehicle crashes and interactions with intersection and off road crashes were also significant. The most significant roadway related variables included speed limit, ADT per lane, access class, lane width, roadway curve, sidewalk width, non-high mast lighting density, type of friction course and skid resistance. The overall model had a very good fit but some misspecification symptoms appeared due to major differences in road entities and crash types by land use. Two additional models of crashes for urban and rural areas were successfully developed. The land use models' goodness of fit was substantially better than any other combination by road entity or the overall model. Their coefficients were substantially robust and their values agreed with scientific or empirical principles. Additional research is needed to prove these results for crash type models found most reliable by this investigation. A framework for injury severity analysis and safety improvement guidelines based on the results is presented. Additional integration of road characteristics (especially intersection) data is recommended for future research. Also, the use of statistical methods that account for correlation among crashes and locations are suggested for use in future research.