Cheung Ivan, Braver Elisa R
a National Transportation Safety Board , Washington, D.C.
b Department of Epidemiology and Public Health , University of Maryland School of Medicine , Baltimore , Maryland.
Traffic Inj Prev. 2016;17(2):202-8. doi: 10.1080/15389588.2015.1034273. Epub 2015 Apr 2.
Prior research suggested that single-unit trucks are undercounted when using vehicle body codes in the Fatality Analysis Reporting System (FARS). This study explored the extent of the misclassification and undercounting problem for crashes in FARS and state crash databases.
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).
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.
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.
先前的研究表明，在使用死亡分析报告系统（FARS）中的车身代码时，单单元卡车被低估。本研究探讨了FARS和州碰撞数据库中碰撞事故的错误分类和计数不足问题的程度。
通过将致命事故中涉及的卡车（TIFA）数据库与FARS进行比较，探讨致命碰撞事故中卡车的错误分类情况。TIFA使用车辆识别号码（VIN）和调查信息对大型卡车进行分类。本研究使用VIN来提高来自5个州（特拉华州、马里兰州、明尼苏达州、内布拉斯加州和犹他州）的州碰撞数据库中大型卡车分类的准确性。
车身类型代码导致FARS中单单元卡车被低估19%，州数据库中单单元卡车被低估23%。牵引式挂车的错误分类较少。错误分类在重量等级为10,001 - 14,000磅的单单元卡车中最为频繁发生。
大型卡车的错误分类数量大到足以潜在地影响联邦和州关于交通安全的决策。使用VIN中的信息可使涉及碰撞事故的大型卡车的计数更完整和准确。国家运输安全委员会建议采取行动改进联邦和州的碰撞数据。
