United States Department of Transportation
i
Evaluation of Software Simulation of Road Weather Information System.
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2016-09-01
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[PDF-1.30 MB]
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Abstract:A road weather information system (RWIS) is a combination of technologies that collects, transmits, models, and disseminates weather and road condition information. Sensors measure a range of weatherͲrelated conditions, including pavement temperature and status (wet, dry, snow), subsurface pavement temperature, wind speed and direction, precipitation, water level conditions, humidity, and visibility. These data are transmitted to automated warning systems, traffic operations centers, emergency operations centers, and road maintenance facilities for decision support. The Enhanced Integrated Climatic Model (EICM) is a computerized heat and moisture flow model that simulates changes in pavement and subgrade properties. It has evolved over the past 40 years and is a key module in the American Association of State Highway and Transportation Officials
(AASHTO) Pavement ME Design software. Using the EICM as a softwareͲbased RWIS can “virtualize” the data that would be gathered by conventional RWIS hardware and software systems. The softwareͲbased RWIS stations would provide current conditions as well as pavement temperature forecasts to supplement or replace hardware in the RWIS network.
The objective of this study was to evaluate the use of the EICM to determine pavement surface temperature for winter maintenance operations. Detailed pavement information at Illinois Department of Transportation, Illinois Tollway, and McHenry County RWIS locations was collected and used to model pavement surface temperatures with the EICM. The modeled pavement surface temperatures were compared with the measured pavement surface temperatures from the RWIS sensors.
Data analysis showed that, when the pavement materials are used at the correct thickness and recommended default values are used for material types, a reasonable pavement surface temperature prediction can be obtained. Using these recommended default values for thermal conductivity, heat capacity, and shortwave absorptivity results in a reasonable modeled pavement temperature that can be used for understanding future snow and ice potential from forecast weather data.
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