ITS数据质量控制技术及应用研究

通过总结智能交通系统 (ITS)数据质量控制中所涉及的数据属性 ,提出了ITS数据质量控制算法 :根据阈值理论和交通流理论 ,针对错误数据、丢失数据和不精确数据设计相应的判别规则 ,利用数值计算方法对其进行修正 ,并提出了针对数据中的不规则时间点的修正算法。在对北京市和美国圣安东尼奥市的两组不同时间序列的ITS数据进行实践应用后 ,比较质量控制前后的数据特征 ,证明所提出的算法能够有效地解决数据质量问题 ,提高数据的精确度。最后 ,对国内外ITS数据进行质量控制后的结论和经验作了总结。

ITS Data Quality Control Techniques and Applications

Through a synthesis of the data characteristics related to the Intelligent Transportation Systems (ITS) data quality control, this paper proposes an ITS data quality control algorithm, which designs the corresponding identifying principles for the erroneous, missing and inaccurate data based on the threshold and traffic flow theories, and utilizes the numerical method to make corrections. Further, a correcting algorithm to the temporal points of ITS data is presented. The comparison of the data characteristics for before and after quality controls, in the applications to two different time series of ITS data from Beijing and San Antonio in U.S. demonstrates that the proposed algorithm can solve the data quality problems effectively, which improves the level of the data accuracy. Finally, a summary is provided to the conclusion and experience on the ITS data quality control.