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https://nap.nationalacademies.org/catalog/27432/critical-issues-in-transportation-for-2024-and-beyond

Automated measurement of road surface defects. Use of distress data in pavement management

Automaattinen paallystevaurioiden mittaus (APVM). Vauriotiedon kaytto paallystetyn tieston yllapidossa

The Finnish Road Administration (Finnra) assesses the condition of the paved public road network by obtaining data on the longitudinal and transverse surface profile, cracking and deflections. Since the beginning of 2006, Finnra has replaced the visual survey of surface cracking with automated interpretation of surface images (APVM) on a two-year contract. The measurement results from the first year, approximately 11 100 km are in the condition data bank of Finnra (CDB). The Finnra experts and designers were interviewed during the procurement process to explore the needs for the use of cracking data. Replacement of existing cracking variables with new ones affects the paved roads management process at several levels and tasks: condition classification, performance targets, maintenance policies, funding needs assessments, and works programming (selection of sections and types of works, and their design). The first task is to familiarise the users with the new variables. Taking new variables into use is also an opportunity for development of practices. There is no true value for the APVM-measurements. Developing the verification procedure is the common task of all involved parties. Paying a fee for acceptable bids enables the testing of the equipment before the actual procurement. The emphasis on R&D -work as part of the measurement contract should be considerably increased. At the same time, the evaluation of bids has to be revised for this part. The Cracked Surface percentage (CS-%) for the lane width (3500 mm) and for the different parts of the lane are taken into the CDB. The CS-indicators are calculated as the number of cracked 200 by 200 mm2 squares divided by the total number of squares. Digital surface images are stored in widely used format for possible future re-interpretation by the same or different vendor. The distributions of the CS- indicators are typical to road condition indicators in that they are skewed to the right. There are a lot of relatively small values and the number of observations decrease with increasing indicator values. Statistical methods used for data analysis usually require that the data is normally distributed, at some point or other. This is achieved fairly well by applying a logarithmic transformation. For the use of results, it is easy to return the original values. The CS- indicators are assigned a lot of zero values, which means that the quality control methods originally developed for the road surface monitoring (RSM) vehicle have to be modified so as to suit better for the APVM. By combining the longitudinal and transverse surface profile with cracking data and by using shorter reporting lengths than 100 m the knowledge of road network condition can be improved, especially of its structural condition. Meanwhile, the same starting point in the longitudinal direction for the various measurements has to be ensured. This report may be found at http://alk.tiehallinto.fi/julkaisut/pdf/3201039-v-voh_automaatt_paallystevaurioiden_mittaus.pdf

Language

  • Finnish

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Filing Info

  • Accession Number: 01043680
  • Record Type: Publication
  • Source Agency: TRL
  • ISBN: 978-951-803-843-9
  • Files: ITRD
  • Created Date: Mar 9 2007 8:08AM