Along with the transformation of transportation system towards autonomous transportation system (ATS), which impels its ability on intelligence and automation consistently and gradually, how to reasonably analyze the evolution across its development stages is essential to support an orderly development. Since the data explodes in the information era, contexts encoded in related knowledge bases become even more complex to be analyzed for the extraction of evolution details. To tackle such a challenge, an evolution analysis mechanism based on the knowledge graph (KG) is proposed to support knowledge modelling, evolution analysis, and information extraction. Moreover, through an evaluation based on a common set of KGs designed to store information about technologies, functions and services to support autonomous driving in different levels, the merits of proposed mechanism are revealed in detecting more accurate evaluations with a reduced number of operations to rebuild the evolutions across KGs.

Ontology;Knowledge Graph;Knowledge Evolution;Autonomous Transportation System