基于AHP灰色理论的道路交通流数据质量评价

Road traffic flow data quality assessment based on grey theory and analysis hierarchical process

交通流信息采集的过程中由于受到设备自身及外在环境等因素的影响,所采集的数据容易出现失真、缺失和冗余等质量问题,无法满足智能化交通管理的要求。本文以准确度、完整度和时效性等3个数据特性作为评价指标,提出了基于层次分析法与灰色聚类分析的道路交通流数据质量评价方法,采用层次分析法确定评价指标的权重,采用灰色系统理论白化权函数建立各指标关联度矩阵模型,结合北京市二环路实测数据进行了实例分析,证明了方法的可行性。

Due to the impact of the equipment failures and the external environment factors, data quality issues such as data distortion, loss, redundancy and so on often occur in the process of road traffic information data acquisition, which is unable to meet the requirements of the intelligent traffic management. In this paper, a method of road traffic data quality assessment was put forward based on the grey theory and analysis hierarchy process （AHP）, in which, 3 data characteristics, such as accuracy, completeness and timeliness, were used as evaluation indexes, AHP method was used to determine the weight of each evaluation index, and the whitening weight function of grey systems theory was used to establish the satisfaction matrix model. The feasibility of the method is proved by the instance analysis of the measured traffic flow data of Beijing＇s second ring road.