Vehicle-to-X Object Data Plausibility Verification
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Solution Overview
Problem
Current methods for protecting object data in vehicle-to-X communication primarily focus on data quality, neglecting the integrity of the data, which can lead to safety-critical traffic situations due to potential manipulation, especially in collective perception scenarios.
Innovation Solution
A method and apparatus that verify the plausibility of object data using map information and sensor information from multiple sources, including vehicle-to-X communication, to ensure the accuracy and reliability of object data, enabling continuous tracking and correction of errors in position and orientation, and providing confidence in the data's trustworthiness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If object data is transmitted via vehicle-to-X communication for collective perception, then the quantity and coverage of detected objects is improved, but the integrity and trustworthiness of the data deteriorates due to potential manipulation
Solution Approach 1:
The patent applies preliminary action by generating a plausibility expectation value before comparing it with the actual object data. The system pre-calculates what the object data should be based on map information and sensor data, then uses this pre-established expectation to verify the integrity of received data, preventing manipulation undetected
Solution Approach 2:
The patent implements feedback by continuously comparing received object data against plausibility expectation values derived from multiple independent sources (map information, sensor data). When discrepancies are detected, the system can request retransmission or alert relevant parties, creating a closed-loop verification system that maintains data integrity
2Reliability
If plausibility checking is performed using multiple data sources, then the reliability of object data is improved, but the complexity of the verification system increases
Solution Approach 1:
The patent applies segmentation by dividing the verification process into distinct modular components: map information processing, sensor data processing, plausibility expectation value generation, and comparison operations. Each component handles a specific aspect of verification independently, making the overall complex system manageable and maintainable
Solution Approach 2:
The patent implements universality by creating a general-purpose plausibility verification framework that can work with multiple types of data sources (map information, sensor data, object data) and apply to various object types. The same verification mechanism serves multiple functions across different scenarios
Data Source
AI summary
A method for protecting the content of data for collective perception and execution by an electronic control apparatus of a first road user including capturing object data, received by means of vehicle-to-X communication, for describing an object detected by at least one capture device of a second road user and/or at least one capture device of an infrastructure device, and checking a plausibility of a state of the object described by the received object data using map information and/or sensor information, wherein the sensor information is determined using sensors of the first road user.