基于多源数据融合，利用关联规则分析中的Apriori算法研究天气条件、路面条件、养护作业等因素与车速变化的关联性，通过速度降低与回复现象有效评估冬季道路养护的效益。结果表明：车速变化与能见度、路面条件和降雪量具有较强关联性，与湿度、风向、工作日、节假日和流量没有相关性。通过数据挖掘技术将存储的多源数据转化为有效的知识和信息，从而可为冬季道路养护提供有效的决策支持。%Based on multi-source data fusion,this study used Apriori algorithm to investigate the association rules between speed reduction and weather condition,pavement condition as well as road maintenance operations. The phenomenon of speed reduction and recovery can prove the mobility benefit of winter maintenance. The results showed that speed reduction has a great association with visibility, pavement condition, snowfall, has not association with humidity,direction of wind,vocation and so on. Data mining technique is useful to transform the abundant of stored data into useful information and knowledge, therefore, it can provide decision-support information for winter road maintenance.
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