The Effect of Weather Events on Truck Traffic Patterns Using Fixed and Mobile Traffic Sensors

Severe weather conditions, i.e. snowfall, floods, ice storms, etc. can have major effects on traffic volumes along the highway network. Unlike passenger vehicles, which may choose not to travel during inclement weather, freight trucks need to adhere to delivery schedules requiring them to alter their route rather than cancel a trip. While previous studies have modeled the effects of weather on total traffic volumes, very few studies have examined the effect of weather on truck volumes. Due to differences in travel behaviors between passenger and freight trucks, the study of weather effects on truck volumes requires advanced modeling techniques that are able to capture effects over space. This study applies spatial regression techniques to develop a predictive model that relates variations in truck traffic patterns to weather conditions, with a focus on extreme weather events. The study uses traffic classification data from six Weigh-in-Motion (WIM) stations and weather data from six weather stations in Arkansas. The study shows that, as expected, reduction in truck volume occurs due to extreme weather events such as snowfall, fog, hail, winter storms, flash flood, etc. Notably, through the spatial model, the negative spatial autocorrelation parameter explains that reductions in truck volume at one site are countered by higher truck volumes at neighboring sites- thus explaining rerouting behaviors of trucks. The study finds extreme cold events (i.e. snow) reduces daily truck volumes by approximately 22% while heavy rainfall, flood, flash flood reduces daily truck volumes by 13%, compared to average daily truck traffic. The study can assist state and regional transportation agencies in developing freight-oriented programs and policies for road and winter maintenance, structural and geometric pavement design, highway life cycle analysis, and long-range transportation planning.

• Record URL:
  https://static1.squarespace.com/static/526c7a98e4b023d8f09390ed/t/5a6b6332c83025a32de421c8/1516987189099/SPTC+15.1-20-F+Hernandez.pdf
• Record URL:
  https://rosap.ntl.bts.gov/view/dot/34828
• Supplemental Notes:
  • This document was sponsored by the U.S. Department of Transportation, University Transportation Centers Program.
• Corporate Authors:

  University of Arkansas, Fayetteville

  Fayetteville, AR  United States 

  Southern Plains Transportation Center

  University of Oklahoma
  201 Stephenson Pkwy, Suite 4200
  Norman, OK  United States  73019

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Authors:
  • Hernandez, Sarah
  • Akter, Taslima
  • Corro, Karla Diaz
• Publication Date: 2017-12-20

Language

• English

Media Info

• Media Type: Digital/other
• Edition: Final Report
• Features: Appendices; Figures; Maps; References; Tables;
• Pagination: 34p

Subject/Index Terms

• TRT Terms: Regression analysis; Sensors; Spatial analysis; Traffic volume; Truck traffic; Weather conditions; Weigh in motion
• Geographic Terms: Arkansas
• Subject Areas: Environment; Motor Carriers; Planning and Forecasting;

Filing Info

• Accession Number: 01661065
• Record Type: Publication
• Report/Paper Numbers: SPTC 15.1-20-F
• Files: UTC, NTL, TRIS, ATRI, USDOT
• Created Date: Feb 23 2018 4:39PM