Lane Data Optimization via Topological Segmentation
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Solution Overview
Problem
Conventional methods for generating digital maps are inefficient in correcting lane data anomalies, particularly in different topological areas, leading to inaccurate lane markings due to issues like gaps, overlapping geometries, and split or merged markings.
Innovation Solution
A system that categorizes lane data based on specific topological areas, applying different models for processing and connecting lane data using a line connector to optimize lane markings, thereby addressing the inefficiencies and inaccuracies in existing methods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single model is used to process lane data of different topologies, then the processing method is simple, but the correction accuracy of lane data is poor
Solution Approach 1:
The patent segments the topological area into multiple regions (first area, second area, and both areas) and applies different processing models to each segment. This allows specialized correction methods for different topology regions, improving accuracy while managing complexity through structured division.
Solution Approach 2:
The patent applies different processing models tailored to specific local regions of the topological area. Each region receives customized processing based on its characteristics, enabling optimized correction accuracy for each local area rather than using a uniform approach.
2Measurement precision
If different models are applied to different topological areas, then the lane data correction accuracy is improved, but the processing complexity increases
Solution Approach 1:
The patent divides the processing task into segments by categorizing locations into distinct groups based on topological area. This segmentation enables different models to be applied to different segments, improving accuracy while organizing complexity through clear categorization and structured processing flow.
3Productivity
If lane data is processed without considering topological area, then the processing speed is fast, but the correction accuracy is low
Solution Approach 1:
The patent performs preliminary categorization of locations into different groups based on topological area before applying processing models. This preliminary action organizes the data structure in advance, enabling efficient targeted processing that maintains speed while significantly improving accuracy through pre-organized categorization.
Data Source
AI summary
The disclosure provides a system, a method, and a computer program product for optimization of lane data. The system may be configured to categorize each location of a set of locations included in the lane data of each lane marking of the plurality of lane markings, into at least one of: a first area or a second area of a topological area. The system may further determine the lane data of each lane marking to be in at least one of: a first group, a second group or a third group, based on each categorized location of the set of locations. The system may further process the lane data associated with each lane marking of the plurality of lane markings based on the determined first group, the second group or the third group.