Key vehicle identification method for traffic congestion on school roads based on knowledge graph

By constructing a hierarchical knowledge graph structure based on knowledge graphs, the problem of cumbersome and time-consuming identification process of key traffic congestion vehicles in the existing technology is solved, and accurate identification and efficient retrieval of key traffic congestion vehicles on the school road section is achieved.

CN117421454BActive Publication Date: 2025-03-18NANJING UNIV OF POSTS & TELECOMM
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Patent Information

Application Number
CN202311311797.2
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2023-10-11
Publication Date
2025-03-18
Estimated Expiration
2043-10-11

AI Technical Summary

Technical Problem

When identifying key vehicles with traffic congestion on the school road section, the data organization and analysis process is cumbersome and time-consuming, and it is difficult to achieve systematic and efficient correlation extraction and feature characterization.

Method used

Using a knowledge graph-based method, a multi-level feature and correlation relationship between individual-level vehicles, roads, travel and school events are constructed, and a knowledge correlation characterization and storage of high-level individual-level features is realized through a hierarchical knowledge graph structure, and accurate identification and efficient retrieval of key vehicles for traffic congestion are carried out.

Benefits of technology

The accurate identification of key vehicles for traffic congestion is achieved, and the identification of each individual vehicle is achieved. It can carefully analyze the vehicle's travel frequency, purpose, and trajectory operation status, and form classified knowledge. The accurate identification of key vehicles for traffic congestion on the school section is achieved through the integration of multiple knowledge.

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Abstract

The present invention discloses a method for identifying key vehicles in traffic congestion on school roads based on knowledge graphs. The knowledge graph technology is introduced, and a hierarchical knowledge graph structure composed of "basic knowledge-feature knowledge formed by reanalysis-discriminant knowledge" is proposed based on individual vehicles as objects. The multi-dimensional and multi-level knowledge generated by the association of multiple objects such as vehicles, roads, travel, and school commuting events is represented in association; at the formation level of feature knowledge, the multi-feature knowledge mining of vehicle travel frequency, purpose, and operating status is used to mine the travel frequency characteristics, purpose characteristics, and trajectory operation characteristics of each vehicle, forming multi-feature knowledge that is integrated into the knowledge graph; under the fusion and discrimination of multi-feature knowledge, the discrimination knowledge of key vehicles of different levels is formed and integrated into the knowledge graph. The present invention realizes the accurate identification of key vehicles in traffic congestion on school roads, and is an information data mining technology for the application of school congestion scenarios in intelligent traffic management.
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