Vehicle Sensor Abnormality Detection via Cross-Sensor Inconsistency
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Solution Overview
Problem
Autonomous vehicle systems face challenges in detecting and addressing sensor abnormalities, which can lead to safety and functionality issues due to sensor defects or security faults, as existing methods may not adequately identify or respond to partial sensor malfunctions.
Innovation Solution
A method that involves receiving measurement values from multiple vehicle sensors, identifying inconsistencies, and taking predefined actions such as disabling nonessential subsystems or the entire vehicle, while also recording defect metadata for pattern analysis and updating error systems to facilitate recalls.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple sensors are used to detect sensor abnormalities through inconsistency analysis, then detection accuracy and reliability are improved, but device complexity increases
Solution Approach 1:
The patent combines data from multiple sensors (first sensor, second sensor, and third sensor) to detect abnormalities. By merging sensor inputs and analyzing inconsistencies between them, the system achieves more reliable abnormality detection while managing complexity through integrated processing logic that compares measurement values across different sensor sources.
2Measurement precision
If comprehensive sensor monitoring and pattern analysis across multiple vehicles is implemented, then identification of defective parts and recall accuracy are improved, but loss of time and computational resources increase
Solution Approach 1:
The patent implements preliminary action by continuously collecting and storing sensor data from multiple vehicles in advance, and pre-processing this data to identify patterns and inconsistencies. When a sensor abnormality is detected, the system can quickly query pre-analyzed data from other vehicles, significantly reducing the time required for defective part identification and recall decision-making.
Solution Approach 2:
The patent uses copying by analyzing sensor data patterns across multiple vehicles with identical or similar sensor configurations. By copying and comparing data from vehicles with the same sensor models and types, the system can identify defective parts through pattern matching, reducing the need for complex real-time analysis of every individual sensor reading.
Data Source
AI summary
Techniques are described with respect to addressing at least one sensor abnormality associated with a vehicle. An associated method includes receiving a first measurement value from a first sensor among a plurality of sensors associated with a vehicle and receiving a second measurement value from a second sensor among the plurality of sensors. The method further includes identifying at least one sensor abnormality based upon an inconsistency between the first measurement value and the second measurement value. In an embodiment, the at least one sensor abnormality results from at least one sensor defect, at least one vehicle security fault, or a combination thereof. The method further includes completing at least one predefined action to address the at least one sensor abnormality.