Multiple lane reduction factors based on multiple lane weigh in motion data

Pierre van der Spuy, Roman Lenner, Tertius de Wet, Colin Caprani

Research output: Contribution to journalArticleResearchpeer-review

Abstract

Multiple lane presence reduction factors are widely used in traffic load models for bridge design to account for the reduced probability of multiple heavy vehicles occurring simultaneously in adjacent lanes. It is custom to reduce the single lane loading by a reduction factor with a value less than one which further reduces as the number of loaded lanes increases. The values of these factors currently published in design codes tend to be based on many assumptions due to previous lack of data. This paper describes a novel method to determine reduction factors based on Extreme Value statistics and multiple lane Weigh in Motion data. The method compares load effects in parallel lanes at characteristic level and avoids traffic composition and multiple presence assumptions made in previous works which were necessary due to the absence of good quality multiple lane data. As the method is based on Weigh in Motion data it also accounts for the possibility of multiple vehicles in any one lane. The method does not rely on dependence or independence between lanes.

Original languageEnglish
Pages (from-to)543-549
Number of pages7
JournalStructures
Volume20
DOIs
Publication statusPublished - 1 Aug 2019

Keywords

  • Bridge loading
  • Generalized extreme value
  • GEV
  • Multiple lane presence
  • Multiple presence reduction factors
  • Weigh in motion

Cite this

van der Spuy, Pierre ; Lenner, Roman ; de Wet, Tertius ; Caprani, Colin. / Multiple lane reduction factors based on multiple lane weigh in motion data. In: Structures. 2019 ; Vol. 20. pp. 543-549.
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Multiple lane reduction factors based on multiple lane weigh in motion data. / van der Spuy, Pierre; Lenner, Roman; de Wet, Tertius; Caprani, Colin.

In: Structures, Vol. 20, 01.08.2019, p. 543-549.

Research output: Contribution to journalArticleResearchpeer-review

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