Movement Variable Determination Using Sensor Confidence Weighting
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Solution Overview
Problem
Existing methods for determining movement-dependent variables, such as position and speed values in toll units and tachographs, lack precision and reliability due to potential sensor manipulation and varying accuracy, which affects the accuracy of the values obtained.
Innovation Solution
A method and device that utilize multiple measured values, each assigned a confidence and accuracy value, which are used to determine the movement-dependent variable by weighting and considering self-diagnosis results and threshold comparisons, employing techniques like Kalman filtering and satellite-based measurements to enhance precision and reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple sensors are used to provide position or speed signals, then the reliability of the determined value improves, but the device complexity increases
Solution Approach 1:
The system divides the sensing function into multiple independent sensors (e.g., GPS receiver, inertial sensors, wheel speed sensors) that each provide separate measurements of the same movement-dependent variable. This segmentation allows the system to cross-validate measurements and detect manipulations while maintaining manageable device complexity through modular architecture.
Solution Approach 2:
The system implements feedback by continuously comparing measurements from multiple sensors and using confidence values to weight and fuse these measurements. The evaluation unit provides feedback on the reliability of each sensor's measurement, allowing the system to dynamically adjust which sensors are trusted and how their data is weighted in the final determination.
2Measurement precision
If confidence values and accuracy values are assigned to each measured value and used for weighting, then the measurement precision improves, but the computational effort increases
Solution Approach 1:
The system changes parameters by assigning confidence values and accuracy values to each measured value based on sensor-specific criteria (e.g., signal strength, historical performance, self-diagnosis results). These parameter changes enable the evaluation unit to weight measurements appropriately, improving precision while the weighting mechanism itself provides a computationally efficient way to handle multiple sensors.
3Reliability
If self-diagnosis of sensors is implemented to adjust confidence values, then the reliability of the determined value improves, but the device complexity increases
Solution Approach 1:
Sensors perform self-diagnosis to assess their own operational status and provide self-evaluation information about their measurement reliability. This self-service approach allows the system to automatically adjust confidence values based on sensor health without requiring complex external monitoring systems, thereby improving reliability while minimizing additional device complexity.
Data Source
Figure 1~2
AI summary
Within the scope of a method for determining a value of a movement-dependent variable (WE), a first measured value (MW_1) representing the movement-dependent variable is provided. In addition, at least one second independent measured value (MW_2) representing the movement-dependent variable is provided. Each measured value (MW_n) is assigned a confidence value (VW_n) representative of a likelihood of the particular measured value (MW_n) being manipulated. The value of the movement-dependent variable (WE) is determined on the basis of the first measured value (MW_1) and at least the second measured value (MW_2) and the particular confidence value (VW_n) thereof.