Trajectory Segmentation with Curve Endpoint Replacement
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Solution Overview
Problem
Conventional methods for segmenting trajectory data often divide straight sections into too many segments and form segmentation points within curve sections, leading to processing delays and potential safety issues in complex traffic situations.
Innovation Solution
A method combining curve smoothing and curve detection algorithms to identify starting and end points of curves, replacing intermediate segmentation points within curve sections with these endpoints, thereby preventing unnecessary segmentation within curves and maintaining consistent segment boundaries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional segmentation methods are applied to trajectory data, then segmentation points are generated based on geometric inconsistencies, but segmentation points are formed within curve sections causing processing delays and safety issues
Solution Approach 1:
The patent applies curve smoothing and generalization algorithms (such as Douglas-Peucker) as a preliminary step before segmentation to simplify the trajectory shape and identify curve sections in advance. This preliminary action allows the system to recognize curve regions before segmentation occurs, preventing segmentation points from being placed within curves and avoiding subsequent processing delays
Solution Approach 2:
The patent introduces an intermediary curve detection mechanism that acts as a mediator between the trajectory data and the segmentation process. This intermediary layer identifies curve sections and provides this information to the segmentation algorithm, enabling it to adjust segmentation point placement and avoid curves, thereby preventing processing delays
2Measurement precision
If conventional segmentation methods are applied to trajectory data, then segmentation points are generated based on geometric inconsistencies, but straight sections are divided into too many segments increasing complexity
Solution Approach 1:
The patent applies different processing strategies to different parts of the trajectory based on local geometric characteristics. Straight sections are segmented using conventional geometric inconsistency detection, while curve sections are identified and protected from segmentation. This local differentiation allows accurate segmentation where needed while avoiding unnecessary segmentation in curve regions, reducing overall complexity
Solution Approach 2:
The patent performs preliminary curve detection and smoothing before the main segmentation process. By identifying curve sections in advance and marking them for protection, the system prevents the segmentation algorithm from creating excessive segments in straight portions adjacent to curves, thereby reducing segmentation complexity while maintaining accuracy
Data Source
AI summary
A method of segmenting trajectory data using a controller. Trajectory data with a plurality of points are received. A Douglas-Peucker algorithm is applied to the trajectory data in order to ascertain substantially straight sections separated by segmentation points. An algorithm is used on the trajectory data in order to detect curves, in the form of starting points and end points of curves. At least one segmentation point ascertained in an interval between a starting point and an end point of a curve is replaced with the starting point and the end point. The trajectory data are segmented at the ascertained segmentation points, the starting points and the end points. A controller, a computer program, and a machine-readable storage medium are also described.