Study of Same-Lane and Inter-Lane GVW Correlation

Bernard Enright, Eugene J. O'Brien, Colin C. Caprani

Research output: Contribution to conferencePaperpeer-review

Abstract

The methodology used is to generate a number of years of simulated traffic and to use extreme value statistics to predict more accurately the characteristic loading for a given bridge. The parameters and probability distributions used in the Monte Carlo simulation must be based on observed sample traffic data. Some previous studies have made unsubstantiated assumptions regarding correlation between the Gross Vehicle Weights (GVW) of trucks in the same lane, or between trucks in adjacent, same-direction lanes. For this paper, an extensive database of Dutch Weigh-in-Motion data is analysed. Data are collected from two same-direction lanes and are time-stamped to the nearest 0.01 seconds. The statistical characteristics of this set of data are presented, and various techniques are used to establish the nature and extent of GVW correlation.
Original languageEnglish
DOIs
Publication statusPublished - 2006
Event3rd International ASRANet Colloquium - Glasgow, United Kingdom
Duration: 1 Jan 2006 → …

Conference

Conference3rd International ASRANet Colloquium
Country/TerritoryUnited Kingdom
CityGlasgow
Period1/01/06 → …

Keywords

  • simulated traffic
  • extreme value statistics
  • characteristic loading
  • bridge
  • Monte Carlo simulation
  • Gross Vehicle Weights
  • GVW
  • trucks
  • same lane
  • adjacent lanes
  • Dutch Weigh-in-Motion data
  • statistical characteristics
  • GVW correlation

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