Road segment traffic state distinguishing method based on multi-source data

The invention discloses a road segment traffic state distinguishing method based on multi-source data. The road segment traffic state distinguishing method comprises the following steps: using traffic parameter values acquired by a fixed detector and a floating car as a data source; selecting historical traffic parameter values and historical traffic state grades in multiple time periods to build a sample database, and calculating an average velocity adjustment parameter of the fixed detector in the smooth traffic period of the road segment, and the road segment historical space average velocity of each period; training to obtain a support vector machine model; respectively adopting a direct judgment method, a K-nearest neighbor nonparametric regression method and a data state correlating analysis method to obtain the road segment space average velocity in the current period; adopting the direct judgment method and the support vector machine model to distinguish the road segment traffic state grade in the current period. According to the road segment traffic state discriminating method disclosed by the invention, the fixed detector and the floating car are used as the data source, and sufficient digging and complementary using are performed on the premise of completely considering the characteristics and the applicability of the data, so that the road segment traffic state discrimination precision is further improved.