Determination of Load Equivalency Factors by Statistical Analysis of Weigh-In-Motion Data

Authors

  • Zoltán Soós Dept of Highway and Railway Engineering, Budapest University of Technology and Economics, Műegyetem quay 3, H–1111 Budapest, Hungary
  • Csaba Tóth Dept of Highway and Railway Engineering, Budapest University of Technology and Economics, Műegyetem quay 3, H–1111 Budapest, Hungary
  • Dávid Bóka Dept of Computer Algebra, Eötvös Loránd University, Pázmány Péter passage 1/C, H–1117 Budapest, Hungary

DOI:

https://doi.org/10.3846/bjrbe.2016.31

Keywords:

EM Algorithm, load equivalency factors, Monte-Carlo simulation, Weigh-in-Motion (WIM).

Abstract

The load equivalency factors for pavement design currently in use by the Hungarian standard have been developed using Weigh-in-Motion data obtained during the first few years of operations after installing some 30 measuring sites in Hungary in 1996. In the past years, and currently, data is collected mainly at the border crossings of the country, however the data is used only for law enforcement purposes, and no comprehensive statistical analyses have been done. To develop actual load equivalency factors for the use in pavement design, data of one year was collected and statistical methods were applied. An algorithm was used to help managing the multimodal distribution of axle loads in mathematical perspectives. Monte-Carlo methods were applied to determine the factors for each heavy vehicle type and eventually for each vehicle class used by the current Hungarian pavement design manual. The calculated factors are considerably different from the current ones, indicating that the pavement design may lead to a false result. Furthermore, there are three vehicle types suggested to be incorporated into the standard due to their high occurrence.

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Published

27.12.2016

How to Cite

Soós, Z., Tóth, C., & Bóka, D. (2016). Determination of Load Equivalency Factors by Statistical Analysis of Weigh-In-Motion Data. The Baltic Journal of Road and Bridge Engineering, 11(4), 266–273. https://doi.org/10.3846/bjrbe.2016.31