一种方向盘生物感知驾驶风险干预系统及方法
By collecting multimodal time-series data and performing effective processing and individual baseline correction, combined with emotion recognition and risk assessment, the instability problem of driver state recognition and risk assessment is solved, and the accuracy of driver state recognition and the safety and stability of active intervention control are achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- RIVOTEK TECH (JIANGSU) CO LTD
- Filing Date
- 2026-05-11
- Publication Date
- 2026-07-17
AI Technical Summary
In the current technology, driver status information is easily affected by dynamic disturbances during driving. Individual differences are significant and the reliability of multi-source status information is inconsistent, resulting in biased recognition results and unstable assessment results. The intensity of intervention is not well matched with the degree of risk, and the timing of intervention exit is unreasonable, which affects vehicle safety and comfort.
By collecting skin conductance signals, electromyographic correlation signals, grip force distribution signals, contact temperature signals, and vehicle behavior signals in the driver's contact area with the steering wheel, raw multimodal time-series data is generated. Distorted samples are processed by weighting using the contact effectiveness coefficient, and individual baseline parameters are established for baseline correction. Combined with emotion recognition and risk assessment, graded active intervention control commands are output.
It improves the accuracy and stability of driver status recognition, enhances the comprehensiveness and rationality of risk assessment, ensures that the intensity of intervention is commensurate with the level of risk, and improves the safety and stability of proactive intervention control.
Smart Images
Figure CN122166114B_ABST