ICASSP 2024accepted0 citations

Modeling Route Representation With Mixed-Scale Hierarchical Transformer

Hanyuan Zhang, Yuqi Chen, Xinyu Zhang, Qize Jiang, Liang Li, Baihua Zheng, Weiwei Sun

Abstract

Modeling route representation aims to obtain contextual representations of an entire route for various traffic-related tasks. In reality, spatial-temporal data often exhibits multi-scale characteristics, which are utilized by many studies to enhance their performance. However, there is still a lack of in-depth research on how to effectively incorporate the multi-scale spatial-temporal information into transformer structure to adequately model route representation. In this paper, we propose a novel hierarchical route representation framework called RouteMT, which effectively captures multi-scale spatial-temporal characteristics of routes and leverages a mixed-scale transformer architecture to fuse intra and interroute features. Experiments on real data confirm RouteMT’s superior performance and versatility.

BibTeX
@inproceedings{icassp2024_modelingrouterep,
  title = {Modeling Route Representation With Mixed-Scale Hierarchical Transformer},
  author = {Hanyuan Zhang and Yuqi Chen and Xinyu Zhang and Qize Jiang and Liang Li and Baihua Zheng and Weiwei Sun},
  booktitle = {ICASSP 2024},
  year = {2024}
}