Method and system for regulating based on traffic prediction data analysis
By acquiring and encoding the differences between traffic prediction data and actual traffic maps, and using deep semantic mining to generate target traffic control strategies, the problem of low control reliability in existing systems is solved, and more flexible and stable traffic control is achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- BAZHONG DATA GROUP CO LTD
- Filing Date
- 2026-05-09
- Publication Date
- 2026-06-09
AI Technical Summary
Existing traffic control systems cannot fully integrate traffic forecast data and actual traffic map data, resulting in an inability to accurately predict traffic flow trends, a lack of flexibility and real-time performance, difficulty in making predictive adjustments based on future traffic flow changes, and low reliability of control.
By acquiring the actual traffic map and predicted traffic data of the target road area, encoding semantic information representing the differences between the predicted traffic data and the actual traffic map, generating a traffic control strategy for the target time, and using deep semantic mining and decoding techniques to constrain and generate the target traffic control strategy.
It improves the reliability and stability of traffic control strategies, enhances their flexibility and real-time performance, and reduces the possibility of deviations from the current control strategy.
Smart Images
Figure CN122176929A_ABST