Virtual WiM: enriching WiM and enhancing decisions 2018–21

NACOE project S26, Virtual WiM – Enriching WiM and Enhancing Decisions identified opportunities for Queensland Department of Transport and Main Roads (TMR) to add value to investments by both TMR and the heavy vehicle transport industry. The project used recent developments in data analytics to link weigh-inmotion (WiM) data with other heavy vehicle datasets to generate new ‘virtual WiM’ or vWiM1 datasets. The vWiM approach enhances data quality, coverage, accessibility, application, and value of TMR’s existing WiM datasets (Figure S 1). The value of vWiM is generated through better evidence-based decisions relating to the $billions invested in transportation and infrastructure made every year while supporting safe productive access to TMR’s infrastructure. The concepts of vWiM emerged while reviewing TMR’s WiM systems, engaging with stakeholders, preparing a draft Strategic Asset Management Plan (SAMP) for WiM, and analysing 13 months of WiM focused on the load platforms, low loaders and cranes. The project demonstrated the viability and value of vWiM concepts by extrapolating WiM data to more common classifier sites across Queensland. In addition, the viability of enhancing the quality of WiM mass data by comparing heavy vehicles of known mass in the traffic stream was demonstrated by integrating GPS tracking, OBM, and ATO data with WiM data. Similarly, bridge monitoring systems were also successfully calibrated using heavy vehicles in the traffic stream. Finally, a prototype tracking tool for Class 1 heavy vehicles was delivered which tracked load platforms posing the greatest risks to bridges through the network to provide a history of loading and inform access and asset management decisions. The project recommends the adoption of the vWiM concepts and supporting a program of continual improvement. The program should target the quality, coverage, accessibility, and linking of datasets. Further development of the engineering and analytics to translate the data into information and knowledge are also necessary to support informed decisions that benefit the Queensland community.

Language

  • English

Media Info

  • Pagination: 175p

Subject/Index Terms

Filing Info

  • Accession Number: 01841399
  • Record Type: Publication
  • Source Agency: ARRB Group Limited
  • Report/Paper Numbers: S26
  • Files: ATRI
  • Created Date: Apr 4 2022 3:33PM