Based on the traffic accident data of Beijing China in 2012, we combined with a variety of municipal administration data, used the geographically weighted regression (GWR) method to study spatial non-stationarity and heterogeneity of the traffic accidents, and analyzed the causes of space regional in traffic accident black spots. Experimental results demonstrated that: (1) The GWR model detects change of the coefficient and explains the significance of coefficient change as well. It is suitable for interpreting the distribution regularity and the causes of traffic accident black spots at the microscopic level. (2) By analyzing the importance of the factors on traffic accident black spots, we note the following order of factors according to the significance: weather, hospital, park, subway station, curvature of the roads and population density. The influence of each factor on traffic accident black spots differs in spatial heterogeneity characteristics.