Remote Sensing of Weather and Road Surface Conditions
Ewan, Levi A.
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Advances in road weather sensing technologies have made noninvasive road weather sensors a valuable component in many intelligent transportation systems (ITS) applications. This study investigates the reliability of using such a sensor for a proposed weather-responsive variable speed limit system. The Vaisala surface state and temperature sensors (DSC-111 and DST-111) were selected for the proposed application. The sensors' ability to provide accurate and reliable data was tested under various conditions in a controlled laboratory environment. Specifically, four outputs of interest from the sensors were tested in this investigation: surface state, snow and ice depth, water depth, and grip level. Testing results showed that the sensors determined the surface state (dry, moist, wet, snowy, and icy) accurately and reliably. The sensors' snow depth readings were found to be inaccurate, while the sensors' ice depth measurements were found to be relatively close to the actual depths. For water depth, only a limited number of readings were close to the actual depths, while other readings were highly inaccurate. In an effort to test the potential of the sensor in providing reliable inputs to the proposed ITS application, a calibration was conducted for the sensor water depth measurements at various water depths and sensor installation angles. Calibration results showed that the water depth could be accurately estimated with the calibrated sensor measurements, regardless of water depth or sensor installation angle. Sensor estimates of grip level were found to be highly correlated to the coefficient of static friction for the conditions considered in this study.
Ewan, Levi, Ahmed Al-Kaisy, and David Veneziano. “Remote Sensing of Weather and Road Surface Conditions.” Transportation Research Record: Journal of the Transportation Research Board 2329, no. 1 (January 2013): 8–16. doi:10.3141/2329-02.