Optimizing automatic traffic recorders network in Minnesota.

Details

• Creators:
  Gupta, Diwakar ; Tang, Xiaoxu
• Corporate Creators:
  University of Minnesota
• Corporate Contributors:
  Minnesota. Dept. of Transportation. Research Services & Library
• Subject/TRT Terms:
  Adjustment Factors Annual Average Daily Traffic Axle Axle Counts Correction Factors Data Processing Equipment Data Recorders Seasonal Adjustment Factors Traffic Counting Traffic Counts
• Publication/ Report Number:
  MN/RC 2016-05
• Resource Type:
  Tech Report
• Geographical Coverage:
  Minnesota ; United States
• Corporate Publisher:
  Minnesota. Dept. of Transportation. Research Services & Library
• Abstract:
  Accurate traffic counts are important for budgeting, traffic planning, and roadway design. With thousands of
  
  centerline miles of roadways, it is not possible to install continuous counters at all locations of interest (e.g.,
  
  intersections). Therefore, at the vast majority of locations, MnDOT samples axle counts for short durations, called
  
  portable traffic recorder (PTR) sites, and obtains continuous counts from a small number of strategically important
  
  locations. The continuous-count data is leveraged to convert short-duration axle counts into average-annual-dailytraffic
  
  counts. This requires estimation of seasonal adjustment factors (SAFs) and axle correction factors at shortcount
  
  locations. This project focused on developing a method for estimating SAFs for PTR sites. The continuouscount
  
  data was grouped into a small number of groups based on seasonal traffic-volume patterns. Traffic patterns at
  
  PTR sites were hypothesized by polling professional opinions and then verified by performing statistical tests.
  
  PTRs with matching seasonal patterns inherited SAFs from the corresponding continuous-count locations.
  
  Researchers developed a survey tool, based on the analytic hierarchy process, to elicit professional judgments.
  
  MnDOT staff tested this tool. The statistical testing approach was based on bootstrapping and computer simulation.
  
  It was tested using simulated data. The results of this analysis show that in the majority of cases, three weekly
  
  samples, one in each of the three seasons, will suffice to reliably estimate traffic patterns. Data could be collected
  
  over several years to fit MnDOT’s available resources. Sites that require many weeks of data (say, more than five)
  
  may be candidates for installation of continuous counters.
  
  
• Format:
  PDF
• Funding:
  (c) 99008 (wo) 112 ; CTS #2013075
• Collection(s):
  US Transportation Collection
• Main Document Checksum:
  urn:sha256:b9d94c726f22e205a6809beab44a01536df9ff09c0208b180a7640156d74218e
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/32175/dot_32175_DS1.pdf
• File Type:
  [PDF - 1.91 MB ]