Intelligent network connected vehicle normalizing supervision hierarchical early warning method

By collecting multimodal data from intelligent connected vehicles to calculate a comprehensive risk index, dynamically adjusting weights, and constructing a parameter dependency graph, the problems of coarse early warning granularity, uneven resource allocation, and inaccurate parameters in the existing regulatory system are solved, thus realizing refined hierarchical early warning and automated supervision.

CN122243222APending Publication Date: 2026-06-19CHINA AUTOMOBILE ZHILIAN TECH CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
CHINA AUTOMOBILE ZHILIAN TECH CO LTD
Filing Date
2026-05-19
Publication Date
2026-06-19

AI Technical Summary

Technical Problem

The existing intelligent connected vehicle monitoring system lacks a dynamic upgrade mechanism, cannot conduct refined graded early warnings based on the severity and scope of the event, resulting in uneven resource allocation, inefficiency due to reliance on manual judgment, inaccurate early warning parameters, and a lack of automated verification and scoring mechanisms.

Method used

By collecting multimodal data, calculating a comprehensive risk index, and dynamically adjusting weights, the system enables event level determination and emergency response. Furthermore, it improves the accuracy of determination through parameter linkage correction and constructs a parameter dependency graph for automated correction.

Benefits of technology

It enables refined, tiered early warning of events involving intelligent connected vehicles, improving response accuracy and resource allocation efficiency, and enhancing the automation level and judgment accuracy of the regulatory system.

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Abstract

This invention discloses a tiered early warning method for routine supervision of intelligent connected vehicles, relating to the field of vehicle data processing. The method includes: acquiring multimodal data of intelligent connected vehicles; calculating a comprehensive risk index based on the multimodal data; determining the current event level and taking appropriate response measures; obtaining feedback on the response results; and adjusting the calculation parameters of the comprehensive risk index based on the feedback results. This invention solves the problem of automated tiered event judgment and response, and improves the accuracy of event level determination through adaptive and linked parameter adjustment.
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