Quantifying uncertainty in real time performance measurement for highway winter maintenance operations - phase 2.

Details

• Creators:
  Lyon, Jillian ; Zhu, Zhengyuan ; Kaiser, Mark
• Corporate Creators:
  Iowa State University. Institute for Transportation
• Corporate Contributors:
  Iowa. Dept. of Transportation ; United States. Federal Highway Administration
• Subject/TRT Terms:
  Mathematical Prediction Performance Measurement Real Time Information Traffic Flow Traffic Speed Weather Conditions Winter Maintenance
• Publication/ Report Number:
  InTrans Project 13-388
• Resource Type:
  Tech Report
• Geographical Coverage:
  Iowa
• Corporate Publisher:
  Iowa State University. Institute for Transportation
• Abstract:
  Winter weather in Iowa is often unpredictable and can have an adverse impact on traffic flow. The Iowa Department of
  
  Transportation (Iowa DOT) attempts to lessen the impact of winter weather events on traffic speeds with various proactive
  
  maintenance operations. In order to assess the performance of these maintenance operations, it would be beneficial to develop a
  
  model for expected speed reduction based on weather variables and normal maintenance schedules. Such a model would allow
  
  the Iowa DOT to identify situations in which speed reductions were much greater than or less than would be expected for a given
  
  set of storm conditions, and make modifications to improve efficiency and effectiveness.
  
  The objective of this work was to predict speed changes relative to baseline speed under normal conditions, based on nominal
  
  maintenance schedules and winter weather covariates (snow type, temperature, and wind speed), as measured by roadside
  
  weather stations. This allows for an assessment of the impact of winter weather covariates on traffic speed changes, and
  
  estimation of the effect of regular maintenance passes.
  
  The researchers chose events from Adair County, Iowa and fit a linear model incorporating the covariates mentioned previously.
  
  A Bayesian analysis was conducted to estimate the values of the parameters of this model. Specifically, the analysis produces a
  
  distribution for the parameter value that represents the impact of maintenance on traffic speeds. The effect of maintenance is not a
  
  constant, but rather a value that the researchers have some uncertainty about and this distribution represents what they know
  
  about the effects of maintenance. Similarly, examinations of the distributions for the effects of winter weather covariates are
  
  possible. Plots of observed and expected traffic speed changes allow a visual assessment of the model fit. Future work involves
  
  expanding this model to incorporate many events at multiple locations. This would allow for assessment of the impact of winter
  
  weather maintenance across various situations, and eventually identify locations and times in which maintenance could be
  
  improved.
  
  
• Format:
  PDF
• Collection(s):
  US Transportation Collection
• Main Document Checksum:
  urn:sha256:b8a0219b89b6d4da36563ede8db6b6ba658ec7dc9465fa0ec14fc29365bb1f01
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/28185/dot_28185_DS1.pdf
• File Type:
  [PDF - 418.89 KB ]