Vehicle Surroundings Data Plausibility Across Redundant Channels
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Solution Overview
Problem
Existing systems for communication and processing of information in autonomous/automated driving are susceptible to errors and manipulations, as they rely on single sensor systems that may fail to verify the integrity and trustworthiness of information sources.
Innovation Solution
A method involving the receipt of multiple redundant information items via different communication channels, followed by plausibility and trustworthiness determination through cross-comparison and assignment to appropriate safety levels for processing, ensuring the integrity and reliability of information used in safety-critical systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple redundant information items are received via different communication channels, then reliability is improved, but device complexity increases
Solution Approach 1:
The system segments information reception by utilizing multiple independent communication channels (first communication connection and second communication connection) to receive different information items (first and second information items, third and fourth information items) about the same surrounding objects. This segmentation allows parallel verification of information integrity without requiring a single complex verification system.
Solution Approach 2:
The system implements feedback through plausibility determination by comparing information items received via different channels. The plausibility assessment feedback mechanism verifies whether the first information item matches the third information item, and whether the second information item matches the fourth information item, thereby confirming data integrity before processing.
2Measurement precision
If plausibility determination through cross-comparison is performed, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The system performs preliminary plausibility determination by comparing information items before they are used for autonomous driving decisions. By pre-verifying that information from different communication channels matches, the system ensures measurement precision is established upfront, preventing later corrections or reprocessing.
Solution Approach 2:
The system merges multiple information items about the same surrounding objects received via different communication channels into a single verified data set. By combining and cross-comparing the first with the third information item, and the second with the fourth information item, the system achieves comprehensive verification efficiently.
3Reliability
If information items are processed according to determined plausibility, then reliability is improved, but device complexity increases
Solution Approach 1:
The system applies local quality by assigning different processing paths to information items based on their determined plausibility. Information items with high plausibility are processed for autonomous driving decisions, while those with low plausibility are rejected or flagged. This localized quality assessment simplifies the overall processing architecture by creating clear decision boundaries.
Data Source
AI summary
A transportation vehicle, computer program, apparatus and method for a transportation vehicle. The method includes receiving a first piece of information and a second piece of information about the surroundings of the transportation vehicle via a first communication connection and a third piece of information and a fourth piece of information about the surroundings of the transportation vehicle via a second communication connection. The first and the third piece of information are different from one another. The second and the fourth piece of information are also different from one another. The method determines a plausibility of the first and the third piece of information by comparing the first and the third piece of information and determines a plausibility of the second and the fourth piece of information by comparing the second and the fourth piece of information and processes at least one of the first to fourth pieces of information.