Vehicle Sensor Signal Redundancy via Dual Processor Fusion
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Solution Overview
Problem
Existing vehicle sensor systems face challenges in achieving high safety levels for measurement signals, requiring significant computational effort and processor performance, while also needing to maintain basic security even if one processor fails, which is resource-intensive.
Innovation Solution
A device with two separate processors to determine comparison signals for sensor fusion, allowing for error detection and correction, and a monitoring processor to ensure continued operation and data integrity by switching to alternative signals or modes if one processor fails, using a Kalman filter for error correction and a cryptoprocessor for security.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a computationally resource-intensive algorithm is used to achieve high security levels (ASIL B or ASIL D) for measurement signals, then the safety level is improved, but the computational effort and processor performance requirements increase significantly
Solution Approach 1:
The system divides the security assurance task into two independent processors (first processor and second processor) that each independently determine comparison signals. This segmentation allows basic security to be achieved through redundancy without requiring a single processor to handle computationally intensive security algorithms, thereby reducing overall computational effort while maintaining safety levels.
2Reliability
If redundant processors are used to ensure basic security levels, then the safety level is improved, but the device complexity increases
Solution Approach 1:
The system uses a second processor that independently determines a comparison signal as a copy/backup of the first processor's function. This copying approach provides redundancy for basic security without requiring complex inter-processor communication or coordination mechanisms, thereby limiting the increase in device complexity while ensuring basic security levels.
3Measurement precision
If sensor fusion is used to increase information content, then the measurement precision is improved, but the computational effort increases
Solution Approach 1:
The system implements partial sensor fusion by using multiple sensors of different sizes to determine comparison signals, but avoids performing complete or excessive fusion operations. The filter device selectively processes data from multiple sensors to provide error correction without requiring full computational fusion of all available sensor data, thereby improving measurement precision while limiting computational resource consumption.
Data Source
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AI summary
The invention relates to a device (4) for outputting a measurement signal (18) indicating a physical measurement variable in a vehicle (2), said device comprising: - a first processor (44) that is designed to determine, on the basis of a first sensor signal (16), a first comparison signal (18) for the physical measurement variable, - a second processor (46) that is designed to determine, on the basis of a second sensor signal (8), a second comparison signal (34) for the physical measurement variable, and - a filter device (30) that is designed to determine an error (40) between the two comparison signals (18, 34) and to output this error to the first processor (44), - wherein the first processor (44) is designed to determine the measurement signal (18) on the basis of a correction of the first comparison signal (18) taking into account the error (40).