Vehicle Sensor Trust Modeling for Reliable Object Detection
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Solution Overview
Problem
Current vehicle operation systems lack effective methods to validate and enhance the integrity of sensor data for object detection, which can impact vehicle safety, especially when using data from heterogeneous sensors.
Innovation Solution
A method that utilizes a trust model to determine a trust value for detected objects based on sensor data, considering the type, state, and environment of the sensors and vehicle, allowing for the validation and fusion of object detections across multiple sensors to improve data integrity and safety.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If sensor data from heterogeneous sensors is used for object detection, then the coverage and detection capability are improved, but the reliability and integrity of object detection deteriorate due to lack of validation
Solution Approach 1:
A trust model is introduced as an intermediary component that validates sensor data from heterogeneous sensors before fusion. The trust model assigns trust values to sensor data based on sensor characteristics, environmental conditions, and data quality metrics, thereby mediating between diverse sensor inputs and the fusion process to ensure reliability
Solution Approach 2:
The system implements feedback mechanisms where trust values are continuously updated based on validation results and performance metrics. The validation process provides feedback about data quality to the fusion system, which adjusts its processing accordingly, creating a closed-loop system that improves reliability through continuous monitoring and adjustment
2Measurement precision
If multiple sensors are integrated for sensor fusion, then the data coverage and detection accuracy are improved, but the system complexity increases
Solution Approach 1:
The validation process is segmented into distinct components: sensor data acquisition, trust model evaluation, trust value assignment, and fusion processing. This segmentation allows each component to be optimized independently and simplifies the overall system architecture by breaking down the complex validation-fusion process into manageable stages
Solution Approach 2:
The trust model serves multiple functions simultaneously: it validates sensor data quality, assigns trust values for fusion weighting, and provides a standardized interface for heterogeneous sensors. This multi-functionality reduces system complexity by consolidating multiple validation and weighting mechanisms into a single universal trust model framework
Data Source
AI summary
In a method of operating a vehicle, sensor data comprising an object detection of a sensor of the vehicle is provided, the object detection being representative of a detected object. Further, a trust model is provided, wherein the trust model is configured to model a trust in object detection. Depending on the sensor data and the trust model, a trust value of the detected object is determined, the trust value of the detected object being representative of how high a trust in the detected object is. The vehicle is operated depending on the trust value of the detected object.