Dynamic Driver State Calibration Using Condition-Based Reference Data
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Solution Overview
Problem
Current vehicle systems require lengthy calibration periods to establish a reliable reference data set for determining driver state variables like attention and fatigue, leading to delayed and potentially inaccurate state determination, as they rely on fixed time windows and neglect special occurrences.
Innovation Solution
A method that dynamically monitors and adjusts conditions during the entire drive to identify suitable situations for recording a reference data set, allowing for continuous updating and rapid calibration of operating parameters based on defined criteria, including ego data, sensor data, and system data from driver assist systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a fixed calibration period is used to determine the reference data set, then the system ensures a baseline period for data collection, but the calibration time is excessively long and the actual function is delayed
Solution Approach 1:
The patent transforms the fixed calibration period into a dynamic process that continuously monitors multiple conditions (driver state, driving situation, sensor availability) and adjusts the calibration status in real-time. The system transitions between different calibration states (not calibrated, partially calibrated, fully calibrated) based on condition satisfaction, eliminating the need for a predetermined fixed time window.
Solution Approach 2:
The system implements continuous feedback by monitoring whether all calibration conditions are met during operation. The calibration status is dynamically updated based on this feedback, allowing the system to transition to full functionality as soon as sufficient reference data is collected, rather than waiting for a predetermined time period to elapse.
2Reliability
If a long calibration period is used to ensure sufficient data, then the reference data set becomes more reliable, but the system performance is reduced during the calibration period
Solution Approach 1:
The patent allows the system to provide partial functionality during calibration. Instead of completely disabling the driver state determination function, the system operates with limited capabilities initially and gradually enhances functionality as calibration conditions are met, avoiding total performance loss while ensuring data quality.
Solution Approach 2:
The system performs preliminary assessments of calibration conditions continuously during operation. By checking whether all conditions are satisfied in real-time and preparing the reference data set incrementally, the system can transition to full functionality more quickly without compromising the reliability of the reference data.
3Reliability
If the calibration period is extended to capture all driving situations, then the reference data becomes more comprehensive, but special occurrences are not properly handled and data quality cannot be ensured
Solution Approach 1:
The patent segments the calibration process into multiple independent conditions (driver state conditions, driving situation conditions, sensor availability conditions) that must all be satisfied. This segmentation allows the system to verify each aspect of data quality separately and ensures that reference data is only collected when all quality criteria are met, rather than relying on a single extended time period.
4Ease of manufacture
If a fixed time window is predetermined for calibration, then the calibration process is simple to implement, but it cannot adapt to whether sufficient data has already been acquired
Solution Approach 1:
The patent replaces the static fixed time window with a dynamic condition-based calibration approach. The system continuously evaluates multiple conditions (driver state, driving situation, sensor availability) and adapts the calibration process accordingly, allowing it to complete calibration faster when conditions are favorable and ensuring data quality when conditions are not met, providing both flexibility and adaptability.
Data Source
AI summary
A method for operating a vehicle system of a motor vehicle for determining at least one state variable which describes the state of the driver, in particular the attention and/or fatigue of the driver, wherein the state variable is determined by using a reference data set which describes a reference state, in particular a normal state of the driver, wherein the conditions of a condition group are verified during an entire drive of the motor vehicle, and wherein when all conditions are established a reference data set is recorded so long as all conditions are established and the reference data set is analyzed for calibrating and/or adjusting at least one operating parameter of the vehicle system.