Detecting Barrier Crossings via Trajectory Density Analysis
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Solution Overview
Problem
Existing digital map systems are ineffective in detecting barrier crossing locations and schedules, particularly for ferry boats and other convoyed objects, due to inaccurate or incomplete data, and lack of methods to exploit the repetitive nature of these crossings.
Innovation Solution
A method to determine barrier crossing information by analyzing historic trajectory data, bundling trajectories with similar geographical and directional properties, and using frequency analysis to identify convoyed objects and derive crossing schedules and frequencies from trajectory density changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional digital map systems are used to detect barrier crossings, then the system structure remains simple, but the detection accuracy and completeness of barrier crossing locations and schedules deteriorates
Solution Approach 1:
The patent segments the complex task of barrier crossing detection into multiple independent processing stages: trajectory data collection, trajectory bundling by spatial and temporal proximity, density analysis, frequency analysis, and barrier crossing identification. Each stage processes a specific subset of data with a specific algorithm, making the overall complex system manageable and modular.
Solution Approach 2:
The patent transforms 2D spatial trajectory data into 3D space-time data by adding the time dimension. Trajectories are analyzed not just in their spatial path but also in their temporal pattern, creating a four-dimensional representation (x, y, z, t) that enables detection of repetitive crossing patterns that would be invisible in traditional 2D map analysis.
2Reliability
If trajectory data from multiple probes is collected and analyzed to improve map accuracy, then the completeness of barrier crossing information improves, but the computational complexity and data processing requirements worsen
Solution Approach 1:
The patent merges multiple trajectory datasets from numerous probes into unified trajectory bundles by combining trajectories that are spatially close and temporally proximate. This consolidation reduces the number of individual data streams that must be processed separately, making the computational load manageable while maintaining comprehensive coverage through the aggregation of multiple data sources.
Solution Approach 2:
The patent performs preliminary processing of trajectory data by pre-bundling trajectories into spatial and temporal groups before conducting the complex frequency analysis. This preliminary organization of data reduces the computational complexity of subsequent analysis by working with pre-grouped data rather than raw individual trajectory records.
3Measurement precision
If existing digital maps are updated with inferred road geometries and features from trajectory data, then the accuracy of navigation information improves, but the time required for map updates and data processing increases
Solution Approach 1:
The patent enables the system to automatically detect barrier crossings, infer road geometries, and update digital maps without requiring manual intervention from map editors. The automated detection algorithms process trajectory data and directly generate map updates, eliminating the time-consuming manual annotation process while maintaining high accuracy through statistical analysis of trajectory patterns.
Data Source
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AI summary
A method for determining barrier crossing information for convoyed objects (22) using historic trajectory data (28). Trajectories (28) having similar geographical and directional properties are bundled so that trajectory density can be measured as a function of position and time (s, t). Visual presentation of the trajectory information can be used to determine certain types of barrier crossing information useful in a digital map. Frequency analysis on a number of trajectory density time series may be performed to determine specific barrier crossing locations (26) through the detection of vehicle bursts. Such frequency analysis may also indicate barrier crossing times and schedules in the case of crossing patterns.