Analysis of the Relationship of Roadside Inspections on Large Truck Crashes

Previous researchers have shed light toward better understanding the relationships among commercial vehicle safety performance, roadside inspection data, and motor carrier’s position (Lantz, B.M. 1993; Britto, R.A., Corsi, T.M., and Grimm, C.M., 2010); however, much of this research is outdated. Moreover, very few previous researchers focused on small motor carriers. There is need to revisit investigating the relationships among a motor carrier’s position (such as size and financial status), safety performance, and roadside inspection data. This research will provide additional evidence on such relationships, especially for various sized motor carriers. In addition, the trend in the relationships will be provided by comparing the most up-to-date analysis with previous ones. This research seeks to investigate crash severity predicting models and contributing factor explorations through the application of data mining models. There are 21 variables found to be associated with commercial truck injury severities. The importance analysis indicates the variable relative important levels for contribution. The top 11 variables account for more than 80% of injury forecasting. For property damage only, the most important variable is “Carrier State,” which indicates that the variable of Carrier State makes the most contributions, as compared with the other variables in explaining property damage only crashes. Variables contribute differently when explaining different crash severities. A variable showing significant importance for a certain severity level may be less crucial for another. For instance, “Cargo Body Type” is the second most important factor for predicting fatality crashes, but is much less important for predicting property damage only crashes (severity=0). However, it is clear that Carrier State is the most influential factor for all severity levels. Marginal effects of important variables are conducted and summarized in the research.

• Record URL:
  https://www.ugpti.org/resources/reports/details.php?id=939
• Record URL:
  https://rosap.ntl.bts.gov/view/dot/42485
• Record URL:
  https://rosap.ntl.bts.gov/view/dot/42486
• Supplemental Notes:
  • This document was sponsored by the U.S. Department of Transportation, University Transportation Centers Program.
• Corporate Authors:

  Mountain-Plains Consortium

  North Dakota State University
  Fargo, ND  United States  58108

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Authors:
  • Lu, Pan
  • Lantz, Brenda
  • 0000-0001-8718-7573
  • Tolliver, Denver
  • Zheng, Zijian
• Publication Date: 2019-4

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References; Tables;
• Pagination: 29p

Subject/Index Terms

• TRT Terms: Compliance; Crash causes; Crash risk forecasting; Crash severity; Data mining; Fatalities; Injury severity; Inspection; Motor carriers; Truck crashes
• Subject Areas: Motor Carriers; Safety and Human Factors;

Filing Info

• Accession Number: 01706819
• Record Type: Publication
• Report/Paper Numbers: MPC 19-381
• Contract Numbers: MPC-475
• Files: UTC, NTL, TRIS, ATRI, USDOT
• Created Date: May 30 2019 9:28AM