MPC Mining Data to Improve Commercial Vehicle Safety
Posted: Jul 1, 2019
MPC researchers at North Dakota State University want to better understand the relationships between roadside inspection data and safety performance data for large trucks. The researchers used data mining techniques and statistical analysis to examine data from the Federal Motor Carrier Safety Administration's Motor Carrier Management Information Systems. They found that trucking company and driver characteristics have significant impacts on truck crash injury severity. An improved understanding about the importance of various factors such as driver characteristics, trucking company characteristics, road conditions, etc. in crash severity will lead to improved safety regulations and enforcement and will help trucking companies take steps to improve operations to reduce risks from those factors that have the greatest impacts on crash severity.
MPC researchers at North Dakota State University want to better understand the relationships between roadside inspection data and safety performance data for large trucks. The researchers used data mining techniques and statistical analysis to examine data from the Federal Motor Carrier Safety Administration's Motor Carrier Management Information Systems. They found that trucking company and driver characteristics have significant impacts on truck crash injury severity. An improved understanding about the importance of various factors such as driver characteristics, trucking company characteristics, road conditions, etc. in crash severity will lead to improved safety regulations and enforcement and will help trucking companies take steps to improve operations to reduce risks from those factors that have the greatest impacts on crash severity.