Vehicle Road Dataset Validation via Confidence Index
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Solution Overview
Problem
Existing vehicle systems lack effective methods to verify the integrity of external database road datasets, which can lead to safety risks due to inaccurate or manipulated data, especially in safety-critical functions like speed regulation and braking control.
Innovation Solution
A method using a communication interface and position determination unit to receive and validate database road datasets by calculating a confidence index based on divergence between external and vehicle road datasets, ensuring data integrity and influencing driving dynamics for enhanced safety.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If database road datasets are used for safety-critical vehicle functions, then vehicle automation and efficiency are improved, but susceptibility to error and safety risks increase due to inaccurate or manipulated data
Solution Approach 1:
The system implements a feedback mechanism by continuously monitoring the agreement between external database road datasets and internally determined vehicle road datasets. When discrepancies are detected, the system adjusts its reliance on external data through the confidence index, creating a closed-loop validation system that enhances data reliability while maintaining automation.
Solution Approach 2:
The confidence index acts as an intermediary element that mediates between external database road datasets and the autonomous driving function. It quantifies the level of trust in external data and influences how much weight is given to external versus internal data sources, thereby protecting the system from erroneous external information while preserving the benefits of automated operation.
2Device complexity
If external database road datasets are used without verification, then device complexity is reduced, but measurement precision and data accuracy deteriorate
Solution Approach 1:
The system performs self-validation by using its own internal road dataset determination capabilities to verify external database road datasets. The vehicle's sensors and processing units independently assess the accuracy of external data without requiring additional external verification systems, thereby maintaining measurement precision while avoiding increased device complexity.
Solution Approach 2:
Instead of implementing a comprehensive verification system for all external data, the system applies partial verification focused on critical parameters where accuracy is most important for safety. The confidence index selectively validates key road dataset elements rather than performing exhaustive checks on all data points, balancing precision requirements with system complexity constraints.
Data Source
AI summary
In a method for operating a vehicle which has a communication interface, a position-determining unit and at least one road data set-determining unit, a database road data set is received by the communication interface, which data set is presumably made available by the database which is arranged externally with respect to the vehicle and which is representative of the position-dependent, road-related property. Depending on the database road data set and a vehicle road data set which is assigned thereto in terms of position, a trust characteristic value is determined which is representative of the level of trust in further database road datasets which relate to predefinable positions of the vehicle.