GCT-TTE: Graph Convolutional Transformer for Travel Time Estimation
Mashurov, Vladimir, Chopurian, Vaagn, Porvatov, Vadim, Ivanov, Arseny, Semenova, Natalia
–arXiv.org Artificial Intelligence
This paper introduces a new transformer-based model for the problem of travel time estimation. The key feature of the proposed GCT-TTE architecture is the utilization of different data modalities capturing different properties of an input path. Along with the extensive study regarding the model configuration, we implemented and evaluated a sufficient number of actual baselines for path-aware and path-blind settings. The conducted computational experiments have confirmed the viability of our pipeline, which outperformed state-of-the-art models on both considered datasets. Additionally, GCT-TTE was deployed as a web service accessible for further experiments with user-defined routes.
arXiv.org Artificial Intelligence
Oct-15-2023
- Country:
- Asia > Russia
- Siberian Federal District (0.19)
- Europe (0.47)
- Asia > Russia
- Genre:
- Research Report (1.00)
- Industry:
- Transportation
- Ground > Road (0.96)
- Infrastructure & Services (1.00)
- Transportation
- Technology: