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Methods: We used data from the International Road Traffic and Accident Database and the Global Burden of Disease project to estimate baseline pedestrian deaths and nonfatal injuries in each country in 2013. The effect of improved passenger car star ratings on probability of pedestrian injury was based on recent evaluations of pedestrian crash data from Germany. The effect of improved heavy motor vehicle (HMV) front end design on pedestrian injuries was based on estimates reported by simulation studies. We used burden of disease methods to estimate population health loss by combining the burden of morbidity and mortality in disability-adjusted life years (DALYs) lost.
Results: Extrapolating from evaluations in Germany suggests that improving front end design of cars can potentially reduce the burden of pedestrian injuries due to cars by up to 24% in the United States and 41% in India. In Germany, where cars comply with the United Nations regulation on pedestrian safety, additional improvements would have led to a 1% reduction. Similarly, improved HMV design would reduce DALYs lost by pedestrian victims hit by HMVs by 20% in each country. Overall, improved vehicle design would reduce DALYs lost to road traffic injuries (RTIs) by 0.8% in Germany, 4.1% in the United States, and 6.7% in India.
Conclusions: Recent evaluations show a strong correlation between Euro NCAP pedestrian scores and real-life pedestrian injuries, suggesting that improved car front end design in Europe has led to substantial reductions in pedestrian injuries. Although the United States has fewer pedestrian crashes, it would nevertheless benefit substantially by adopting similar regulations and instituting pedestrian NCAP testing. The maximum benefit would be realized in low- and middle-income countries like India that have a high proportion of pedestrian crashes. Though crash avoidance technologies are being developed to protect pedestrians, supplemental protection through design regulations may significantly improve injury countermeasures for vulnerable road users. 相似文献
Methods: Truck misclassifications for fatal crashes were explored by comparing the Trucks Involved in Fatal Accidents (TIFA) database with FARS. TIFA used vehicle identification numbers (VINs) and survey information to classify large trucks. This study used VINs to improve the accuracy of large truck classifications in state crash databases from 5 states (Delaware, Maryland, Minnesota, Nebraska, and Utah).
Results: The vehicle body type codes resulted in a 19% undercount of single-unit trucks in FARS and a 23% undercount of single-unit trucks in state databases. Tractor-trailers were misclassified less often. Misclassifications occurred most frequently among single-unit trucks in the weight classes of 10,001–14,000 pounds.
Conclusions: The amount of misclassification of large trucks is large enough to potentially affect federal and state decisions on traffic safety. Using information from VINs results in more complete and accurate counts of large trucks involved in crashes. The National Transportation Safety Board recommended actions to improve federal and state crash data. 相似文献