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:
  • Winter maintenance
  • Real time information
  • Performance measurement
  • Traffic speed
  • Traffic flow
  • Weather conditions
  • Mathematical prediction
• 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.
  More +
• Format:
  PDF
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/28185/dot_28185_DS1.pdf
• File Type:
  [PDF - 418.89 KB]
• Collection(s):
  US Transportation Collection
• Main Document Checksum:
  urn:sha256:b8a0219b89b6d4da36563ede8db6b6ba658ec7dc9465fa0ec14fc29365bb1f01