详情

原文传递 RESULTS OF AV WINTER ROAD CONDITION SENSOR PROTOTYPE.

题名：	RESULTS OF AV WINTER ROAD CONDITION SENSOR PROTOTYPE.
作者：	McFall-K; Niittula-T
关键词：	Acoustic-detectors; Classification-; Hybrid-simulation; Icy-roads; Image-processing; Neural-networks; Road-weather-information-systems; Sensors-; Signal-processing; Snow-cover; Winter-
摘要：	After several years of research in winter road condition classification, an automated prototype has been tested. Classification is achieved with artificial neural networks based on data from either images of the road, acoustic signals of vehicles passing the sensors, or a combination of the two. Systems based on either images or signals give good results for some road condition classes, but the most reliable results are for the hybrid system. Hybrid results are reliable for icy, snowy, and wet road conditions but not for dry. Dry results can be improved with more representative training data and/or further integration with other RWIS sensors. For days with icy, snowy or wet conditions, the classification system gives near 100% correct classification for all but 3 days during a 3-month winter period.
总页数：	Conference Title: 11th International Road Weather Conference (http://www.sirwec.org). Location: Sapporo, Japan. Sponsored by: Standing International Road Weather Commission. Held: 20020126-20020128. 2002/01. pp8
报告类型：	科技报告