DBSCANSD

Rust implementation for DBSCANSD, a trajectory clustering algorithm.

Brief Introduction

DBSCANSD (Density-Based Spatial Clustering of Applicationswith Noise considering Speed and Direction)[1] is a clustering algorithm extended from DBSCAN [2]. It can consider speed and direction, which is essential for maritime lanes extraction. The output of this algorithm is a set of Gravity Vectors (GV) and Sampled Stopping Points (SSP).

Since the AIS data provided for this project is confidential, I cannot upload it to github as example. But I generated a toy data set and put it in the src folder which can be tested with the program. And it will be great if you use this algorithm for other domains' problems, such as tracking data of vehicles, pedestrian, hurricane or animals.

More details about this algorithm can be found in [1]. The link is as following:

http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7004281

and a Java implementation for DBSCANSD, the link is as following:

https://github.com/luborliu/DBSCANSD

Reference

[1] Liu, Bo, et al. "Knowledge-based clustering of ship trajectories using density-based approach." Big Data (Big Data), 2014 IEEE International Conference on. IEEE, 2014.

[2] Ester, Martin, et al. "A density-based algorithm for discovering clusters in large spatial databases with noise." Kdd. Vol. 96. No. 34. 1996.