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首页> 外文会议>International Truck amp; Bus Safety Research amp; Policy Symposium, Apr 3-5, 2002, Knoxville, Tennessee, USA >AN ANALYSIS OF COMMERCIAL VEHICLE DRIVER TRAFFIC CONVICTION DATA TO IDENTIFY HIGH SAFETY RISK MOTOR CARRIERS
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AN ANALYSIS OF COMMERCIAL VEHICLE DRIVER TRAFFIC CONVICTION DATA TO IDENTIFY HIGH SAFETY RISK MOTOR CARRIERS

机译：商业车辆驾驶员交通对流数据分析，以识别高安全风险机动车辆

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摘要

This project explores the idea of using commercial motor vehicle driver traffic conviction data from the Commercial Driver License Information System (CDLIS) to help identify high safety risk motor carriers. Prior research and intuitive knowledge suggest that certain types of motor carriers may employ drivers with higher than average traffic conviction rates. This study should help to provide new knowledge of high-risk carriers, and allow better focusing of enforcement efforts to reduce crashes and fatalities on the highways. Because there is not a national traffic citation database, and there are substantial problems with state or local police officers accurately identifying the employing motor carrier when issuing a traffic citation, a direct approach of using citation data for analysis is not feasible nationwide. Therefore, the present project studies whether a correlation exists between traffic conviction data (a subset of citations), accessible through CDLIS, and high risk motor carriers linked to drivers through inspection and crash reports contained in the Motor Carrier Management Information System. This study concludes that linking driver conviction data to the employing motor carrier provides a method to identify those motor carrier companies with safety problems. A carrier driver history measure created based on the average number of convictions of drivers associated with the carriers is significantly correlated with carriers' out-of-service rates, accident rates, and SafeStat Safety Evaluation Area (SEA) scores. Carriers with higher (worse) driver history measures are also more likely to have higher OOS rates, accident rates, and SEA scores.
机译：该项目探索了使用来自商业驾驶执照信息系统（CDLIS）的商业驾驶者交通定罪数据来帮助识别高安全风险驾驶者的想法。先前的研究和直觉知识表明，某些类型的机动车辆可能雇用的驾驶员的交通定罪率高于平均水平。这项研究应有助于提供有关高风险承运人的新知识，并可以更好地集中执法力度，以减少高速公路上的撞车和死亡事故。因为没有国家交通引用数据库，并且州或地方警察在发布交通引用时准确识别要使用的机动运输工具存在实质性问题，因此在全国范围内无法直接使用引用数据进行分析。因此，本项目研究可通过CDLIS访问的交通定罪数据（引用的子集）与通过载具管理信息系统中包含的检查和碰撞报告链接到驾驶员的高风险载具之间是否存在相关性。这项研究得出的结论是，将驾驶员的定罪数据链接到雇用的汽车运输公司提供了一种识别那些存在安全问题的汽车运输公司的方法。根据与承运人相关的驾驶员的平均定罪次数创建的承运人驾驶员历史记录测度与承运人的服务中断率，事故率和SafeStat安全评估区域（SEA）分数显着相关。具有较高（更糟）驾驶员历史记录的措施的航空公司也更有可能具有较高的OOS发生率，事故率和SEA分数。

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