A vehicle operation safety intelligent management method and system based on multi-source perception

By integrating environmental, vehicle, and driving data through multi-source perception and parallel risk model calculation, the problem of accurately quantifying complex risks in existing technologies has been solved, enabling efficient and accurate early warning for the vehicle operation safety management system.

CN122196785APending Publication Date: 2026-06-12SHANDONG RUITE LOGISTICS CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
SHANDONG RUITE LOGISTICS CO LTD
Filing Date
2026-03-10
Publication Date
2026-06-12

AI Technical Summary

Technical Problem

Existing vehicle operation safety management systems cannot effectively integrate multi-source data from the environment, vehicles, and drivers, making it difficult to accurately quantify complex risks. This results in delayed or missed warnings and fails to meet the safety management needs in complex scenarios.

Method used

By acquiring environmental, vehicle, and driving data through multi-source perception, a parallel risk model is used to calculate the risk coefficient. Combined with hierarchical mapping and coupling coefficient correction, two parallel computing methods are formed. The higher risk level is taken as the final risk level, and prompt information and voice warnings are generated.

Benefits of technology

It enables comprehensive perception and accurate identification of multi-source risks, improves the accuracy and robustness of risk identification, and ensures timely early warning under complex risk conditions.

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Abstract

The application discloses a kind of based on multi-source perception's vehicle operation safety intelligent management method and system, belong to data processing field, based on multi-source perception's vehicle operation safety intelligent management method includes following steps: through networking interface or man-machine interaction obtains environmental data, environmental data is converted into environmental risk coefficient according to weather risk contrast table;Vehicle data is obtained by on-board diagnostic system and sensor, compared with prior art, the beneficial effects of the present application are: the present application realizes the comprehensive perception of environment, vehicle, driving risk by multi-source data fusion, adopts parallel risk model to calculate vehicle and driving risk coefficient, and truly reflects the nonlinear superposition effect when multiple sub-risks coexist;The comprehensive risk value is calculated by the maximum risk and coupling coefficient correction, combined with risk level matrix determination, form two parallel computing modes, and take the higher one as the final risk level, significantly improve the accuracy and robustness of risk discrimination.
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