| Autor: |
Vladimir Mashurov, Vaagn Chopuryan, Vadim Porvatov, Arseny Ivanov, Natalia Semenova |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Journal of Big Data, Vol 11, Iss 1, Pp 1-14 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2196-1115 |
| DOI: |
10.1186/s40537-023-00841-1 |
| Popis: |
Abstract 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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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