Vehicle Sensor Self-Diagnosis for Degradation Monitoring
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Solution Overview
Problem
Existing automated driving technologies do not account for sensor degradation due to aging or malfunction, which can affect sensing performance and lead to inaccurate obstacle detection.
Innovation Solution
A control device and method that acquires sensing results and positional information from a sensor-equipped vehicle, detects specified objects within a reference distance, and determines sensor performance using the sensing results, allowing for real-time assessment and correction of sensor degradation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If sensor performance is assumed to be accurate without verification, then the automated driving control system operates simply, but sensor degradation due to aging or malfunction goes undetected leading to unreliable sensing
Solution Approach 1:
The sensor performs self-diagnosis by detecting a specified object (diagnosis target object) and comparing the detection result with expected values. The sensor itself generates diagnosis information about its own performance status, enabling autonomous health monitoring without requiring complex external verification systems.
Solution Approach 2:
The control device receives diagnosis information from the sensor and uses it to adjust or control the automated driving operation. This feedback loop allows the system to respond to sensor degradation by modifying driving behavior, ensuring safety while maintaining operational continuity.
2Measurement precision
If sensor degradation is not monitored, then the system operates with fewer functions, but sensing accuracy deteriorates over time due to aging and environmental factors
Solution Approach 1:
The sensor autonomously performs self-diagnosis by detecting a specified object and evaluating its own detection accuracy. This self-service mechanism enables continuous monitoring of sensing performance without requiring separate diagnostic sensors or manual verification, maintaining measurement precision while preserving automation functionality.
3Reliability
If the system continuously monitors sensor performance by detecting specified objects, then sensor degradation is detected accurately, but computational load and processing time increase
Solution Approach 1:
The system extracts only the necessary diagnostic information from sensor data by focusing on detection accuracy of a specified object rather than processing all sensor outputs. This selective approach enables effective sensor performance monitoring while minimizing computational load and processing time.
Data Source
AI summary
A control device (100) can communicate with a first sensor (300) for detecting an object around a first vehicle and is equipped on the first vehicle (500). The control device (100) includes a first acquisition unit, a second acquisition unit, a detection unit, and a determination unit. The first acquisition unit acquires a sensing result being a result of detecting an object around the first vehicle (500) from the first sensor (300) equipped on the first vehicle (500). The second acquisition unit acquires positional information of a specified object being an object for performance measurement of the first sensor (300). The detection unit detects the specified object existing within a reference distance from the first vehicle (500), by use of positional information of the first vehicle (500) and positional information of the specified object. The determination unit determines performance of the first sensor (300), based on the sensing result of the specified object by the first sensor (300).