Speed Sign Classification Using Sensor-Map Comparison
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Solution Overview
Problem
Current navigation systems fail to provide accurate conditional speed sign information for segments with varying speed limits due to incomplete or outdated map data, leading to potential hazards for vehicles traversing conditional road segments.
Innovation Solution
A system and method that classify speed signs as conditional or non-conditional by comparing sensor data with map data, using processors to determine the presence of conditional speed signs and update map data in real-time, ensuring accurate navigation assistance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If map data is used for navigation assistance, then route guidance is provided, but conditional speed sign information is incomplete or outdated
Solution Approach 1:
The system captures images of speed signs using sensors on the vehicle, processes these images to extract speed limit information, and uses this feedback to update the map data. This closed-loop feedback mechanism ensures that the map data remains current and accurate, resolving the contradiction between information completeness and navigation safety
Solution Approach 2:
The system enables the navigation application to automatically update its own map data by processing sensor data from speed signs encountered during normal operation. This self-service approach allows the system to maintain current information without external intervention, improving both information completeness and reliability
2Measurement precision
If sensor data is processed in real-time, then accurate speed sign classification is achieved, but system complexity increases
Solution Approach 1:
The system segments the speed sign recognition task into distinct components: image capture by sensors, image processing to extract speed limit information, comparison with existing map data, and classification as conditional or non-conditional. This segmentation allows each component to be optimized independently while maintaining overall accuracy without excessive complexity
Solution Approach 2:
The system uses a multi-functional approach where the same processing pipeline handles both capturing speed sign images and processing them for classification. The navigation application serves multiple functions: route guidance, speed sign detection, data processing, and map updating. This universality reduces overall system complexity while maintaining measurement precision
Data Source
AI summary
A system, method and computer program product are provided for classifying at least one speed sign associated with a region. In an example embodiment, the method may include obtaining sensor data comprising speed limit data associated with the at least one speed sign. The method may further include obtaining map data associated with a segment of the region, wherein the map data comprises conditional speed limit data associated with a conditional speed limit sign linked with the segment. The method may further include comparing the speed limit data with the conditional speed limit data and classifying the at least one speed sign as one of a conditional speed sign or a non-conditional speed sign based on the comparison.