Planar Graph Generation for Open Space Path Analysis
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Solution Overview
Problem
Existing path analysis methods struggle to obtain accurate results when the paths to be analyzed in spatial data are unknown, particularly in open spaces where people can move freely, as they require pre-defined maps or mesh divisions, which are not feasible in all scenarios.
Innovation Solution
A planar graph generation device and method that computes a specific value representing the complexity and non-nearness of track data, selects the track with the smallest value, and generates addition target track data by approximating portions within a specific distance, reducing computation load while maintaining precision.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If track data are superimposed one by one to generate planar graphs, then the planar graph can be generated without pre-defined maps, but the computation load increases significantly
Solution Approach 1:
The patent segments the track data collection into multiple subsets and processes them in parallel to generate multiple planar graphs simultaneously, rather than sequentially superimposing all track data one by one. This division of computation reduces the overall computation load while maintaining the ability to generate accurate planar graphs in open spaces without pre-defined maps.
2Measurement precision
If all track data are processed to generate accurate planar graphs, then high precision is achieved, but the processing time increases
Solution Approach 1:
The patent performs preliminary processing by dividing track data into subsets and pre-generating multiple planar graphs in parallel before final integration. This preliminary action allows the system to maintain high precision in vehicle position reflection while significantly reducing the overall processing time through concurrent computation.
3Device complexity
If track portions within specific distance are approximated, then computation load is reduced, but potential loss of track detail information occurs
Solution Approach 1:
The patent applies approximation selectively only to track portions that are within a specific distance of each other, while preserving detailed information in regions where tracks are well-separated. This local quality approach reduces computation load for overlapping regions without losing important track detail information in distinct regions.
Data Source
AI summary
A planar graph generation device that includes a processor that executes a process. The process includes: computing a specific value, including components of a value representing complexity of a track of the given track data, and a value representing a non-nearness between the given track data and each of all the other track data; selecting the track data with the smallest specific value among the collection; a first portion of the first track or a second portion of the second track positioned within the specific distance of each other, or a combination of the first portion and the second portion, is approximated to a specific portion such that a track of the addition target track data after addition passes through the specific portion in cases in which there are portions positioned within the specific distance of each other in a combination of the first track with the second track.