Multi-detail traffic cell division method and system based on spectral clustering algorithm

The invention discloses a multi-detail traffic cell division method and system based on a spectral clustering algorithm. The method comprises the following steps: S1, constructing an undirected weighted graph of a target area road network; S2, respectively calculating a road network similarity matrix contributed by each vehicle travel track; S3, summing the road network similarity matrixes contributed by all vehicle travel tracks to obtain a similarity matrix; S4, calculating the degree of each road section in the undirected weighted graph and constructing a degree matrix; S5, constructing a Laplace matrix based on the degree matrix and the similarity matrix, calculating characteristic values of the Laplace matrix, and taking characteristic vectors corresponding to the characteristic values to form a characteristic matrix; S6, taking the feature matrix as a sample, and performing clustering by using a Kmeans method. According to the method, the road sections with high correlation in daily travel of residents