Space-time fusion method for natural language expressing dynamic traffic information

Disclosed is a temporal-spatial fusion method for a natural language to express dynamic traffic information, comprising the following steps: to make data pre-processing to the dynamic traffic information described in the form of Chinese natural language to eliminate errors or invalid information; to take the pre-processed result as an input parameter to improve the maximum matching algorithm and segment the key words in the algorithm; then to make use of the address positioning vocabulary reconstruction method to process the address positioning vocabularies and organize each key word based on the time, location, direction, offset and the structure of the event so as to express the dynamic traffic information in a formalized way; to process the formally expressed traffic key words through a temporal-spatial matching method facing the information fusion, and to ultimately achieve the purpose of temporal-spatial fusion between the dynamic traffic information and the underlying road network information. The method of the invention has the advantages of intelligence, automation, strong fault-tolerant capability, high fusion accuracy and wide adaptability, which solves the common problem of difficult real-time matching and fusion between the dynamic traffic information described in natural language and the underlying road network spatial information.