Navigation Path Prediction Using Trajectory Clustering and Road Correction
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Solution Overview
Problem
Conventional navigation systems face errors in position information due to GPS inaccuracies and improper collection cycles, leading to incorrect path predictions for mobile objects like ships, airplanes, and vehicles.
Innovation Solution
A navigation system that uses a path controller to identify and cluster moving trajectories based on points of interest and behavior, applying a road correction mechanism to extract a corrected moving path by calculating similarity functions and reflecting road information, thereby minimizing errors in GPS position information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS position information is used directly for path prediction, then the navigation system is simple to operate, but the position information contains errors leading to incorrect path predictions
Solution Approach 1:
The system performs preliminary clustering of moving trajectories and pre-processing of position information before final path prediction. By clustering trajectories in advance and organizing them into structured data, the system prepares corrected position information that can be directly used for accurate path prediction without adding complex real-time processing
Solution Approach 2:
The patent introduces an intermediary clustering mechanism that acts as a mediator between raw GPS position information and final path prediction. The clustering module processes and corrects position information through intermediate steps (clustering similar trajectories, identifying moving sections), thereby improving accuracy without requiring the entire system to be fundamentally complex
2Speed
If the GPS position information collection cycle is increased to improve real-time path prediction, then the path prediction responsiveness is improved, but the position information errors increase due to longer time intervals
Solution Approach 1:
The system uses feedback from clustered trajectory data to continuously refine position information. By comparing current position data with previously clustered trajectories and using this feedback to correct deviations, the system maintains high accuracy even with faster collection cycles, as the feedback mechanism compensates for any errors introduced by increased sampling frequency
3Reliability
If conventional GPS position information is used without correction, then the navigation system requires minimal processing, but the path prediction contains errors that cannot be corrected
Solution Approach 1:
The patent segments the path prediction process into distinct modules: trajectory clustering, moving section identification, and path prediction. Each module handles a specific aspect of position information processing independently, making the overall complex system manageable and maintainable while achieving reliable error-free path predictions through systematic segmentation of processing tasks
Data Source
AI summary
A navigation terminal includes a path controller configured to identify moving trajectories reaching respective points of interest, to cluster the identified moving trajectories into at least one moving section, to reflect a road correction mechanism in the at least one clustered moving section and to cluster the at least one clustered moving section into at least one moving path, and to extract one moving path, in which time sequential position information received from a GPS is corrected, from the at least one clustered moving path. Thereby, the navigation terminal is resistant to error of a GPS sensor, error generated due to a collection cycle, or error generated in correction, and precisely predicts a moving path.