The application belongs to the
cross field of
traffic engineering and
information technology, and discloses a highway continuous longitudinal slope section traffic
safety knowledge graph construction method.The method integrates section characteristics,
traffic flow, historical accidents and
environmental data, and constructs a multi-
source data set through cleaning and
standardization processing; defines section, accident, environment and vehicle entities, and constructs a multi-level
knowledge graph containing a static topology layer, a dynamic attribute layer and a probability reasoning layer; uses
natural language processing technology to extract knowledge triples, combines with a
rule engine to dynamically fuse the correlation logic of slope, environment and accident data, realizes real-time
risk assessment and early warning; uses a
graph database to store the graph, supports
semantic query and dynamic update.The application breaks through the limitations of traditional single
data source analysis, solves the
coupling risk assessment problem of dynamic environmental factors and static characteristics under complex
terrain through multi-source fusion and probability reasoning mechanism, and significantly improves the traffic
safety risk prediction accuracy.