In order to effectively extract typical traffic scenes from massive natural driving data, a method for recognizing and extracting driving scenes is proposed based on driving behavior primitives. To address the challenges of being limited to extracting only a specific single scene and the inefficiency of scene retrieval from large-scale data acquisition, the paper developed an automatic recognition and extraction framework for typical driving scenes. This framework ensures multi-class scene coverage and features high degree of universality.