DETECTION OF PREFERENTIAL ICING ON BRIDGES, USING TRAFFIC AND METEOROLOGICAL DATA
"Preferential Icing" is the phenomenon in which a highway bridge, but not grade-level approach roadway, is covered by ice. Since attempts to detect preferential icing directly have been only partly successful, this research was under taken to assess the feasibility of inferring the presence of preferential icing from traffic speed patterns and local meteorological data. In order to test the feasibility of detecting ice from traffic data, a field experiment was run on a rural bridge on Wyoming State Highway 34. The electronic field hardware recorded the speed and deceleration patterns of vehicles approaching and crossing the bridge, and several meteorological data, including solar radiation, air, road, and bridge temperatures, humidity, and wind speed and direction. Ice was detected by a time-lapse movie camera focused on part of the bridge deck and approach road. The study demonstrated that, on short bridges traveled primarily by local residents, the difference between vehicle speed patterns on dry and on icy pavement is too small and variable to permit the inferential detection of bridge icing. However, it appears feasible to detect snow from traffic speeds, since average speeds are about 10 mph (16 km/h) lower when the pavement is covered by snow. /FHWA/
- Sponsored by the Department of Transportation, Federal Highway Administration, Office of Environmental Control.
Technology Service Corporation2811 Wilshire Boulevard
Santa Monica, CA USA 90403
- Eldon, J A
- Publication Date: 1978-9
- Pagination: 111 p.
- TRT Terms: Bridge decks; Detection and identification; Detectors; Icing; Motor vehicles; Nitrogen compounds; Speed; Traffic speed
- Subject Areas: Highways; Operations and Traffic Management;
- Accession Number: 00188964
- Record Type: Publication
- Source Agency: Federal Highway Administration
- Report/Paper Numbers: FHWA-RD-78-134 Final Rpt.
- Contract Numbers: DOT-FH-11-8278
- Files: TRIS, USDOT
- Created Date: Apr 12 1979 12:00AM