Decentralized risk decision sending method and system

By coordinating decision-making between vehicle terminals and roadside edge nodes, risk decision-making instructions are calculated and sent in real time, solving the latency problem caused by centralized early warning on cloud platforms, achieving efficient risk early warning and decision-making, and improving the real-time performance and accuracy of the system.

CN121600748APending Publication Date: 2026-03-03AXERA SEMICON (SHANGHAI) CO LTD
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Patent Information

Application Number
CN202610098201.2
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-01-26
Publication Date
2026-03-03

AI Technical Summary

Technical Problem

In existing vehicle-road-cloud integrated systems, the centralized early warning method through the cloud platform is prone to decision delays when facing massive and high-concurrency real-time traffic data, resulting in delayed risk warnings and failing to meet the requirements of high real-time risk warning scenarios.

Method used

A decentralized risk decision sending method is adopted, which uses vehicle terminals and roadside edge nodes to make collaborative decisions and distributed processing to calculate the current risk value and predicted risk value of the vehicle in real time. When the risk value exceeds the threshold, risk decision instructions are sent directly to the vehicle, reducing the dependence on the cloud platform.

Benefits of technology

It improves the real-time nature and response speed of risk warnings, reduces the risk of traffic accidents, avoids data transmission and calculation delays, and improves the accuracy and efficiency of risk warnings.

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Abstract

The invention relates to the technical field of driving early warning, and provides a decentralized risk decision sending method and system, and the method comprises the steps: calculating a current risk value of each vehicle terminal through first road condition data collected by a vehicle terminal and second road condition data collected by a roadside edge node based on all driving objects in a monitoring range; and calculating a predicted risk value corresponding to each current risk value through the risk early warning model, determining risk information when the predicted risk value is greater than or equal to a risk threshold value, and sending a corresponding risk decision instruction to the vehicle terminal based on the risk information. Tasks of data acquisition, risk value calculation and the like are dispersed to the vehicle terminal and the roadside edge node, so that the delay and calculation pressure of data transmission are effectively reduced, the real-time performance and response speed of risk early warning are improved, and the traffic accident risk caused by early warning lag is reduced.
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