Time-Aware Contrastive Representation Learning for Road Network and Trajectory

Ashraful Islam Shanto Sikder, Naushin Nower

2025

Abstract

Modeling and learning representations for road networks and vehicle trajectories is essential for improving various Intelligent Transportation System (ITS) applications. Existing methods often treat road network and trajectory data separately, focus only on one, employ two-step processes that result in information loss and error propagation, or ignore temporal dynamics. To address these limitations, we propose a framework called Time-Aware Contrastive Representation Learning for Road Network and Trajectory (TCRLRT). Our approach introduces an end-to-end model that simultaneously learns road network and trajectory representations, enhanced by a temporal encoding module that captures temporal information and a synthesized hard negative sampling module to enhance the discriminative power of the learned representations. We validate the effectiveness of TCRLRT through extensive experiments conducted on two real-world datasets, demonstrating improved performance over baseline methods across multiple downstream tasks. The results highlight the advantages of joint representation learning with temporal modeling and hard negative sampling, leading to robust and versatile representations.

Paper Citation

in Harvard Style

Sikder A. and Nower N. (2025). Time-Aware Contrastive Representation Learning for Road Network and Trajectory. In Proceedings of the 11th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS; ISBN 978-989-758-745-0, SciTePress, pages 498-505. DOI: 10.5220/0013297700003941

in Bibtex Style

@conference{vehits25,
author={Ashraful Sikder and Naushin Nower},
title={Time-Aware Contrastive Representation Learning for Road Network and Trajectory},
booktitle={Proceedings of the 11th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS},
year={2025},
pages={498-505},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013297700003941},
isbn={978-989-758-745-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS
TI - Time-Aware Contrastive Representation Learning for Road Network and Trajectory
SN - 978-989-758-745-0
AU - Sikder A.
AU - Nower N.
PY - 2025
SP - 498
EP - 505
DO - 10.5220/0013297700003941
PB - SciTePress