Abstract: Floating car technique is an effective means for obtaining aggregated road network operating speeds data,but the processed ones can not reflect the real speed due to the original data collecting errors,which can be attempted to solve by data fusion method.Basing upon three levels of data fusion,three levels are proposed,including filtering data errors by association analysis,taking advantages of the fusion of statistical speed with historic database to deal with inadequate sample representativeness of floating cars,as well as fusing data of floating cars with static detectors to address the problem of the vehicle speed processing under complicated road network circumstances．

摘要： 利用浮动车技术可以方便地获取路网车速,但由于采集的原始数据存在误差等原因,使得处理后的车速不能反映路网实际车速,利用数据融合技术可以解决这些问题。结合数据融合的三个级别,提出利用关联检验的方法过滤误差数据,利用统计车速与历史库车速的融合解决由于浮动车少造成车速代表性差的问题,利用浮动车同固定检测器的融合解决复杂路网下车速的处理问题。