Location Trace Data Adjustment for Road Geometry Accuracy
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Solution Overview
Problem
Service providers and device manufacturers face challenges in accurately and efficiently processing large volumes of geographical location information for digital maps and advanced driver assistance systems, as manual methods for marking maneuvers during data collection are often inaccurate due to vehicle speed and conditions.
Innovation Solution
A system that processes imaging data associated with location trace data to determine maneuvering information for vehicles, allowing for adjustments to the location trace data to improve the accuracy of road geometry and centerline detection, using algorithms and sensors like GPS/IMU and cameras to automatically validate and correct data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual methods are used to mark maneuvers during data collection, then the process is simple to operate, but the accuracy of maneuver detection deteriorates due to vehicle speed and conditions
Solution Approach 1:
The patent replaces manual mechanical marking operations with an automated optical-mechanical system. Cameras mounted on the vehicle capture images of road markings, and image processing algorithms automatically detect lane changes and maneuvers, eliminating the need for manual marking while significantly improving accuracy.
Solution Approach 2:
The system enables self-service maneuver detection by automatically processing its own collected imaging data to identify maneuvers. The vehicle's own camera system and processing algorithms work together to detect lane changes without external assistance, improving both accuracy and operational efficiency.
2Measurement precision
If automated processing of imaging data is implemented, then maneuver detection accuracy improves, but device complexity increases
Solution Approach 1:
The patent implements a multi-functional processing system that handles multiple tasks: capturing imaging data, detecting road markings, identifying maneuvers, and adjusting location trace data. This universal system consolidates what could be separate complex functions into an integrated solution, managing complexity while maintaining high accuracy.
Solution Approach 2:
The patent introduces an intermediary image processing layer between the camera system and maneuver detection. This intermediary layer processes raw imaging data to extract meaningful features (road markings, lane boundaries) before maneuver identification, simplifying the overall system architecture while improving detection accuracy.
3Manufacturing precision
If location trace data is adjusted based on maneuvering information, then the accuracy of road geometry improves, but processing time increases
Solution Approach 1:
The patent performs preliminary adjustment of location trace data at the point of maneuver detection. By immediately correcting location data when maneuvers are identified, rather than performing batch processing later, the system reduces overall processing time while maintaining high geometric accuracy.
Solution Approach 2:
The patent applies adjustments locally only to portions of location trace data affected by maneuvers, rather than processing the entire dataset. This selective approach focuses computational resources on critical segments, improving road geometry accuracy where needed while minimizing overall processing time.
Data Source
AI summary
An approach is provided to process imaging data associated with location trace data of one or more links of a road. A processing platform may process and/or facilitate a processing of imaging data associated with location trace data of at least one link of a road to determine maneuvering information for at least one vehicle collecting the imaging data, the location trace data, or a combination thereof. Further, the processing platform may determine whether to cause, at least in part, an adjusting of at least a portion of the location trace data based, at least in part, on the maneuvering information.