Route Contour Matching Using Intersection Angle Sequences
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Solution Overview
Problem
The manual design of personalized running routes is time-consuming and labor-intensive due to the complexity of road network data, making it difficult for users to create special and interesting routes without extensive effort.
Innovation Solution
A method and apparatus that acquire route description information from users, match it with road network data using intersection points and angle sequences, and generate recommended routes by mapping and scaling the route contour, allowing for various input methods such as drawing, image import, or text descriptions, and providing a route recommendation interface for navigation and tracking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual design method is used for personalized routes, then route customization is achieved, but time consumption and labor intensity increase significantly
Solution Approach 1:
The system pre-processes road network data to extract intersection information, angle sequences, and spatial relationships before the user actually needs to design a route. This preliminary structuring of data enables rapid matching when the user provides route description information, eliminating the need for manual, time-consuming route design while preserving full customization capability.
Solution Approach 2:
Instead of manually designing routes from scratch, the system creates copies of existing road network structures by matching the user's desired route shape (contour) against pre-extracted road intersection patterns. The algorithm finds corresponding intersections in the real road network that match the geometric characteristics of the user's desired route, automatically generating a realizable route that replicates the user's intended path.
2Adaptability or versatility
If manual design method is used for personalized routes, then route customization is achieved, but labor intensity increases significantly
Solution Approach 1:
The system performs self-service by automatically matching user-desired route shapes with actual road network data without requiring manual intervention. The algorithm independently extracts intersection points, calculates angle sequences, and finds corresponding routes in the road network, completely automating what would otherwise require significant human effort in manually plotting and adjusting routes on maps.
Solution Approach 2:
The patent replaces the mechanical manual process of route design (where users would manually plot routes on maps) with an automated computational system. The system uses algorithms to extract geometric features from user input, compare them against pre-processed road network data, and automatically generate route recommendations, substituting human manual labor with machine-based automated processing.
3Manufacturing precision
If route contour matching is performed with high precision, then route accuracy is improved, but computational complexity increases
Solution Approach 1:
The system extracts only the essential geometric features (intersection points and angle sequences) from both the user's desired route contour and the road network data, rather than processing complete route geometries. This extraction of key distinguishing features enables accurate matching while significantly reducing computational complexity by focusing only on the most important characteristic elements.
Solution Approach 2:
The route matching process is segmented into distinct stages: first extracting intersection points from the route contour, then calculating angle sequences for each intersection, and finally matching these segmented features against pre-processed road network intersections. This segmentation of the matching process into discrete, manageable steps reduces overall computational complexity while maintaining high route matching accuracy.
Data Source
AI summary
The present application discloses a method and apparatus for determining a route, a device and a computer storage medium, and relates to the field of big data. An implementation includes: acquiring route description information input by a user, and acquiring a route contour with the route description information; matching the route contour in road network data to obtain the route matched with the route contour, so as to generate recommended routes, wherein this operation specifically includes: extracting intersection points in the route contour, each of which is formed by intersecting at least two lines; selecting one of the intersection points, and querying the road network data using a corresponding angle sequence of the selected intersection point in the route contour, so as to obtain intersections matched with the selected intersection point as candidate intersections; traversing the candidate intersections, fixedly mapping the selected intersection point to the positions of the candidate intersections, equally scaling the route contour in the road network data, and recording mapped road information if all lines of the route contour are mapped onto connected roads; and generating the recommended routes with the recorded road information.