The application belongs to the technical field of automatic driving, and particularly relates to a driving behavior semantic
library construction method, a
scenario-based retrieval method and a
system for automatic driving. The driving behavior semantic
library constructed by taking the
codebook of a trajectory segmenter as a driving behavior
semantic dictionary fully taps the potential value of the
codebook and solves the problem of insufficient semantic utilization in the prior art. By preprocessing,
cutting and converting massive historical driving data into compact Token sequences, storage overhead is greatly reduced, while key behavior
semantics are retained, and efficient utilization of historical data is realized. The semantic
library based on multi-level indexing supports fast
scenario-based retrieval, so that the
system can retrieve the
processing strategy of a similar historical
scenario in real time when facing rare corner cases, and provide reliable online decision assistance for an end-to-end model. The
retrieval result can be directly used to automatically generate diversified
simulation test cases, changing the situation of inefficient and limited coverage of traditional manual design.