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Protocols for Collecting and Using Traffic Data in Bridge Design (2011) / Chapter Skim
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Pages 106-112

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From page 106...
... The study also gives practical examples of implementing these protocols with recent national WIM data drawn from states/sites around the country with different traffic exposures, load spectra, and truck configurations. Truck traffic data should be collected through WIM systems that simultaneously can collect headway information as well as truck weights and axle weights and axle configurations while remaining hidden from view and unnoticed by truck drivers.
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From page 107...
... The one implemented in these protocols is based on the assumption that the tail end of the histogram of the maximum load effect over a given return period approaches a Gumbel distribution as the return period increases. The method assumes that the WIM data are assembled over a sufficiently long period of time, preferably a year, to ensure that the data are representative of the tail end of the truck weight histograms and to factor in seasonal variations and other fluctuations in the traffic pattern.
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From page 108...
... Load effects for following trucks may be obtained directly from the WIM data where accurate time arrival stamps are collected. Generalized multiple-presence statistics obtained in Step 6 may be used for simulation of load effects where accurate truck arrival time stamps are not available.
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From page 109...
... The results of these sensor calibration tests will be the basis for filtering out WIM measurement errors for each WIM data site. The protocols present a procedure to filter out the WIM calibration errors from the measured WIM histograms of gross weights (or load effects)
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From page 110...
... However, as discussed in Step 13, using a single maximum or characteristic value for Lmax for a state would be acceptable if the scatter or variability in Lmax from site to site for the state was equal to or less than the COV assumed in the LRFD calibration. The site-to-site scatter in the Lmax values obtained from recent WIM data showed significant variability from span to span, state to state, and between onelane and two-lane load effects -- well above the overall 20% COV used during the LRFD calibration.
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From page 111...
... • DOTs should carefully consider the locations of WIM sites within a state. Remote WIM sites away from weigh stations are needed to provide unbiased WIM data.
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From page 112...
... • Separating permit vehicles from non-permit traffic in large-scale WIM data requires the availability of a reliable electronic permits database/records of special permits authorized in a given period for a state. DOT surveys have indicated that such permit databases are not currently being maintained, at least in an electronic form.
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Key Terms

  • reliability index
  • wim data
  • wim sites
  • simple span
  • monte carlo

  • load effects
  • fatigue truck
  • load effect
  • wim sensor
  • headway separation

  • lmax values
  • return period
  • carlo simulation
  • time stamp
  • maximum load

  • axle weight
  • lrfd calibration
  • permit truck
  • measured wim
  • sensor errors

  • annual permits
  • average reliability
  • aashto lrfd
  • fatigue damage
  • permit vehicle

  • adjacent lanes
  • permit trucks
  • illegal trucks
  • axle load
  • load models


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