Trajectory Similarity Analysis with the Weight of Direction and k-Neighborhood for AIS Data
Bibliographic Data
| ID | 22032819 |
|---|---|
| Authors | Pin Nie (0000-0002-9492-2940, Nanjing University), Zhenjie Chen (0000-0002-3033-8470, Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, corresponding author), Nan Xia (0000-0002-2000-6018, Nanjing University), Qiuhao Huang (Nanjing University), Feixue Li (0000-0001-7234-7191, Nanjing University) |
| Year | 2021 |
| Volume | 10 |
| Issue | 11 |
| Pages | 757 |
| Publication date | 2021-11-10 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | ISPRS International Journal of Geo-Information (JOURNAL) |
| Journal identifiers | ISSN: 2220-9964 • E-ISSN: 2220-9964 |
| Publisher | MDPI AG (PUBLISHER • IT) |
| DOI | 10.3390/ijgi10110757 |
| OpenAlex | W3212612973 |
| Language | EN |
| Citations received | 1 |
| References cited | 43 |
Automatic Identification System (AIS) data have been widely used in many fields, such as collision detection, navigation, and maritime traffic management. Similarity analysis is an important process for most AIS trajectory analysis topics. However, most traditional AIS trajectory similarity analysis methods calculate the distance between trajectory points, which requires complex and time-consuming calculations, often leading to substantial errors when processing AIS trajectory data characterized by substantial differences in length or uneven trajectory points. Therefore, we propose a cell-based similarity analysis method that combines the weight of the direction and k-neighborhood (WDN-SIM). This method quantifies the similarity between trajectories based on the degree of proximity and differences in motion direction. In terms of its effectiveness and efficiency, WDN-SIM outperformed seven traditional methods for trajectory similarity analysis. Particularly, WDN-SIM has a high robustness to noise and can distinguish the similarities between trajectories under complex situations, such as when there are opposing directions of motion, large differences in length, and uneven point distributions
Algorithm · Data mining · Trajectory · Computer Science · Data Management and Algorithms · Human Mobility and Location-Based Analysis · Maritime Navigation and Safety · Mathematics · Artificial Intelligence
| Unique citing works | 1 |
|---|---|
| Citations per year | 0.25 |
| Citation span | 2022 - 2022 (1) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 1 |