Data fusion processing method for dynamic time granularity of multiple traffic detection sources

The invention discloses a data fusion processing method for the dynamic time granularity of multiple traffic detection sources, and belongs to the technical field of urban traffic data analysis. The method comprises the following steps: detecting the data acquisition time interval to extract a time base; loading space information for detection data, and generalizing the data structure of traffic data; evaluating the data correlation degree, equipment data accuracy and environment influence degree of each detection source to obtain the credibility coefficient of the detection source; obtaining the time granularity application requirement based on dynamic changing and updating of location check-in data of a mobile terminal in a detection area; and carrying out traffic parameter fusion of the multiple detection sources according to the application requirement and the credibility of the detection sources. According to the invention, urban traffic data processing based on the traffic data acquired by a basic sensor and the location check-in data of the mobile terminal is in line with the development trend of big data, and the rate of dynamic data fusion according to the change of time granularity is effectively improved. The method has the advantages of quick operation getting and storage redundancy reduction.