Name
Title | ||
|---|---|---|
Short-term trajectory prediction for individual metro passengers integrating diverse mobility patterns with adaptive location-awareness |
Abstract | ||
|---|---|---|
•This study extends diverse mobility knowledge and real-time location-awareness into the short-term trajectory prediction for individual metro passengers.•A new encoding method is proposed to reflect the diverse mobility patterns for individual metro passengers, which include temporal periodicity, spatial symmetry, and sequence correlation.•This is a prospective attempt to achieve the short-term trajectory prediction of individual metro passengers using real-world Wi-Fi probe data at the metro station level.•The proposed StTP-ML model can integrate more interpretable mobility patterns and provide more accurate predicted trajectories. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1016/j.ins.2022.03.074 | Information Sciences |
Keywords | DocType | Volume |
Intelligent transportation system,Short-term trajectory prediction,Wi-Fi probe data,Mobility pattern,Variable n-gram model | Journal | 599 |
ISSN | Citations | PageRank |
0020-0255 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jinjing Gu | 1 | 0 | 0.34 |
| Z. B. Jiang | 2 | 242 | 36.08 |
| Wei Fan | 3 | 0 | 0.34 |
| Jingjing Chen | 4 | 0 | 0.34 |