Curve-Shape Modeling Device for Steady Section Length Accuracy
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Solution Overview
Problem
Existing navigation systems fail to accurately model road shapes, particularly steady sections, leading to inadequate vehicle speed control and driving support, as they cannot digitize steady section lengths accurately.
Innovation Solution
A curve-shape modeling device that classifies sampling points into linear, relaxation, and steady sections by extracting curves based on curvature, determining steady section curvature, and setting a curvature range to identify start and end points of steady sections, preventing excessive shortening of steady sections and enabling accurate curve shape modeling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If map data is generated based on actual vehicle travel routes using prior art methods, then route information can be obtained, but the steady section length cannot be digitized accurately leading to excessive shortening of steady sections
Solution Approach 1:
The patent segments the vehicle travel route into distinct sections (linear section, relaxation curve section, and steady section) based on curvature characteristics. By dividing the continuous route data into these functional segments, the system can accurately identify and measure the steady section length without confusion from adjacent curve sections, thereby resolving the measurement accuracy problem while maintaining reliable curve shape modeling.
Solution Approach 2:
The patent uses curvature as a key parameter to identify and delineate steady sections. By calculating curvature values from the vehicle's travel data and comparing them against threshold values, the system can automatically detect the start and end points of steady sections. This parameter-based approach enables precise digitization of steady section lengths, preventing excessive shortening while ensuring accurate curve shape representation for driving support.
2Device complexity
If curve extraction is performed without considering curvature range, then processing is simpler, but steady sections are shortened excessively
Solution Approach 1:
The patent introduces curvature threshold parameters to define the boundaries of steady sections. By setting minimum and maximum curvature values that characterize steady sections, the system can filter and identify these sections automatically during curve extraction. This parameter-based filtering adds minimal complexity to the extraction process while effectively preventing excessive shortening of steady sections by maintaining their true lengths.
3Productivity
If sampling points are processed without curvature-based classification, then processing is faster, but accurate curve shape modeling cannot be achieved
Solution Approach 1:
The patent segments sampling points into different categories (linear, relaxation curve, steady section) based on their curvature characteristics. This segmentation allows the system to process each type of point with appropriate algorithms, maintaining high processing speed while achieving accurate curve shape modeling. The classification enables efficient identification of steady sections without requiring complex processing of all sampling points uniformly.
Solution Approach 2:
The patent uses curvature calculation as a key parameter to classify sampling points into different section types. By computing curvature values for each sampling point and comparing them against predefined thresholds, the system can rapidly categorize points and identify steady sections. This parameter-driven approach maintains processing efficiency while enabling precise curve shape modeling, as the curvature parameter directly reflects the geometric characteristics of the road.
Data Source
AI summary
A curve-shape modeling device that divides multiple sampling points along a route into a linear section, a relaxation curve section and a steady section, and models a curve shape of the route, includes: a curve extraction unit that extracts a curve from the sampling points based on a curvature of the sampling points; a steady section curvature determination unit that determines a curvature of the steady section based on a curvature of sampling points included in an extracted curve; and a curve entry and exit determination unit that sets a predetermined curvature range including the curvature of the steady section, and determines a start point and an end point of the steady section based on the curvature range.