Motor Carrier Safety: A Statistical Approach Will Better Identify Commercial Carriers that Pose High Crash Risks than Does the Current Federal Approach

摘要

The Federal Motor Carrier Safety Administration (FMCSA) has the primary federal responsibility for reducing crashes involving large trucks and buses that operate in interstate commerce. FMCSA decides which motor carriers to review for compliance with its safety regulations primarily by using an automated, data-driven analysis model called SafeStat. SafeStat uses data on crashes and other data to assign carriers priorities for compliance reviews. GAO assessed (1) the extent to which changes to the SafeStat model could improve its ability to identify carriers that pose high crash risks and (2) how the quality of the data used affects SafeStat's performance. To carry out its work, GAO analyzed how SafeStat identified high-risk carriers in 2004 and compared these results with crash data through 2005. While SafeStat does a better job of identifying motor carriers that pose high crash risks than does a random selection, regression models GAO applied do an even better job. SafeStat works about twice as well as (about 83 percent better than) selecting carriers randomly. SafeStat is built on a number of expert judgments rather than using statistical approaches, such as a regression model. For example, its designers decided to weight more recent motor carrier crashes twice as much as less recent ones on the premise that more recent crashes were stronger indicators of future crashes.