Road Sign Data Synchronization Using Reliability Factors
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Solution Overview
Problem
Conventional driver assistance systems face challenges in providing unambiguous and accurate road sign information due to outdated digital map data and varying reliability of road-sign recognition devices, often resulting in contradictory information that is not optimally processed.
Innovation Solution
Assigning reliability factors to road-sign data from both digital maps and recognition systems to determine which data to output, prioritizing data from the camera when conditions are favorable and from the map when conditions are poor, ensuring accurate and consistent information delivery to the driver.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If road sign information is provided from digital maps, then comprehensive road sign coverage is achieved, but information accuracy deteriorates due to outdated map data
Solution Approach 1:
The system merges road sign information from two sources: digital maps and camera-based recognition devices. By combining these sources, the system achieves both comprehensive coverage (from maps) and high accuracy (from real-time camera recognition), resolving the contradiction between quantity and reliability of information.
Solution Approach 2:
The system uses camera-based road sign recognition as feedback to verify and update map data. When the camera detects road signs that differ from or are not present in the map data, this feedback triggers an update mechanism, ensuring map information remains current and accurate while maintaining comprehensive coverage.
2Reliability
If road sign recognition is performed using camera-based devices, then information up-to-dateness is improved, but measurement reliability deteriorates under varying ambient conditions
Solution Approach 1:
The system introduces map data as an intermediary reference to validate and supplement camera-based recognition. When ambient conditions affect camera recognition accuracy, the map data serves as a reliable intermediary source to cross-verify detected road signs, maintaining measurement precision while preserving the up-to-dateness advantage of camera-based systems.
3Quantity of substance
If contradictory information from map and recognition device is processed, then complete information availability is achieved, but information ambiguity increases
Solution Approach 1:
Instead of treating map data as the primary source and camera recognition as supplementary, the system inverts this approach by treating real-time camera recognition as the primary source and map data as supplementary verification. This inversion resolves information ambiguity by prioritizing current observational data over potentially outdated map information, while still maintaining complete information availability through cross-referencing.
Data Source
AI summary
A method for recognizing road signs in the vicinity of a vehicle and for synchronization thereof to road sign information from a digital map where, in the case of a recognition of road signs, road-sign recognition data are generated, navigation data being provided for localizing the vehicle in digital map data, and the road-sign recognition data being synchronized to the map data. To be able to provide unambiguous and the most accurate possible and thus improved road sign information to be output to the driver in the context of such a method, in the case of a discrepancy between the map data and the road-sign recognition data, the decision is made with the aid of reliability factors for the camera and map as to whether the data from the digital map or the road-sign recognition data are output in the vehicle.