Modeling Road Surface Temperature from Air Temperature and Geographical Parameters—Implication for the Application of Floating Car Data in a Road Weather Forecast Model

This research examines floating car data (FCD) and the collection, via sensor, of air temperature (Tₐ) measurements for use with road weather forecasts. It focuses on thermal mapping based on data collected in Sweden from busy roads over one winter season. The results identify several repeatable thermal fingerprints during times of high traffic intensity with different weather patterns. The spatial patterns of the thermal fingerprints were influenced by real-time weather pattern, previous weather patterns, and measurement time. The influence of urban density, altitude, shading, and sky-view factor on road surface temperature (RST) and Tₐ measurements is also discussed. The regression models with Tₐ outperformed models based only on geographical parameters and explained up to 82% of the RST distribution.

Language

  • English

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Filing Info

  • Accession Number: 01716086
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Jul 17 2019 4:26PM