AAAI 2024technical3 citations
TelTrans: Applying Multi-Type Telecom Data to Transportation Evaluation and Prediction via Multifaceted Graph Modeling
ChungYi Lin, Shen-Lung Tung, Hung-Ting Su, Winston H. Hsu
Abstract
To address the limitations of traffic prediction from location-bound detectors, we present Geographical Cellular Traffic (GCT) flow, a novel data source that leverages the extensive coverage of cellular traffic to capture mobility patterns. Our extensive analysis validates its potential for transportation. Focusing on vehicle-related GCT flow prediction, we propose a graph neural network that integrates multivariate, temporal, and spatial facets for improved accuracy. Experiments reveal our model's superiority over baselines, especially in long-term predictions. We also highlight the potential for GCT flow integration into transportation systems.
BibTeX
@article{Lin_Tung_Su_Hsu_2024, title={TelTrans: Applying Multi-Type Telecom Data to Transportation Evaluation and Prediction via Multifaceted Graph Modeling}, volume={38}, url={https://ojs.aaai.org/index.php/AAAI/article/view/30331}, DOI={10.1609/aaai.v38i21.30331}, abstractNote={To address the limitations of traffic prediction from location-bound detectors, we present Geographical Cellular Traffic (GCT) flow, a novel data source that leverages the extensive coverage of cellular traffic to capture mobility patterns. Our extensive analysis validates its potential for transportation. Focusing on vehicle-related GCT flow prediction, we propose a graph neural network that integrates multivariate, temporal, and spatial facets for improved accuracy. Experiments reveal our model’s superiority over baselines, especially in long-term predictions. We also highlight the potential for GCT flow integration into transportation systems.}, number={21}, journal={Proceedings of the AAAI Conference on Artificial Intelligence}, author={Lin, ChungYi and Tung, Shen-Lung and Su, Hung-Ting and Hsu, Winston H.}, year={2024}, month={Mar.}, pages={22927-22933} }