Instructions for Use
The similarity measurement of the line trajectory dataset uses the search dataset to find the trajectory line that is most similar to the search trajectory from the trajectory dataset. Returns trajectory data that is most similar to the search trajectory. The result dataset will retain all attribute fields of the trajectory data, and will also add "QueryFeatureID", "SimilarityFeatureID", and "Similarity" fields. The "QueryFeatureID" field is used to represent the feature field values of the search trajectory object; The 'SimilarityFeatureID' field is used to represent the feature field values of the resulting trajectory object; The "Similarity" field is used to represent the similarity or distance between trajectories, where all point objects belonging to the same search object query have the same similarity value. The provided trajectory similarity measurement methods include: *Hausdorff distance: based on the measurement method of track shape, the similarity is determined by calculating the maximum distance of the nearest point between two tracks. The condition is that the number of points between two tracks cannot differ too much. *Frechet Distance: Based on the idea of track dynamic programming, similar to the dog rope distance, the similarity is determined by calculating the longest distance between two tracks at the same time, which is sensitive to noise. *Dynamic time warping DTW: the point based measurement method has no limit on the track length, and has good effect, but is sensitive to noise. *MaxSimilarLength: This method is time constrained and only searches for trajectories within the same time period as the search trajectory. !
Parameter Description
| Parameter Name | Default Value | Parameter Definition | Parameter Type |
|---|---|---|---|
| Line Trajectory Dataset | Trajectory Dataset: Finds the trajectory that is most similar to the search trajectory from the trajectory dataset, must be a line dataset, and must have a unique feature ID | FeatureRDD | |
| Search Dataset | As a reference dataset, find the trajectory that is most similar to the search trajectory from the trajectory dataset, which must be a line dataset and have a unique feature ID | FeatureRDD | |
| Trajectory similarity measurement method (Optional) |
Maximum similarity length | Trajectory similarity measurement method, please refer to the Instructions for Use | JavaSimilarityAlgorithm |
| Returns the number of most similar trajectories (Optional) |
5 | Returns the number of most similar trajectories, which must be greater than 0 | Int |
| Space distance tolerance (Optional) |
50 meters | If the trajectory measurement method is the maximum similar length, the space distance tolerance is expressed as the maximum error distance between two points, that is, when the distance between two points is greater than the tolerance value, similarity is impossible. For other track measurement methods, tolerance represents the error of the minimum bounding rectangle of the track object, that is, when the minimum bounding rectangle of two tracks intersects under the tolerance error, the distance between tracks is calculated, otherwise it is not calculated | JavaDistance |