Origin-Destination Travel Time Oracle for Map-based Services
Summary: DOT is a diffusion-based two-stage framework for OD travel-time estimation from historical trajectories. Stage 1 uses a conditioned Pixelated Trajectories denoiser to learn OD-time correlations; Stage 2 applies a Masked Vision Transformer to estimate travel time with outlier removal, boosting accuracy, scalability, and explainability on real data. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Yan Lin (Beijing Jiaotong University)
- 2. Huaiyu Wan (Beijing Jiaotong University)
- 3. Jilin Hu (East China Normal University)
- 4. Shengnan Guo (Beijing Jiaotong University)
- 5. Bin Yang (East China Normal University)
- 6. Youfang Lin (Beijing Jiaotong University)
- 7. Christian S. Jensen (Aalborg University)
BibTeX Citation
@inproceedings{lin_sigmod23,
title = {{Origin-Destination Travel Time Oracle for Map-based Services}},
author = {Lin, Yan and Wan, Huaiyu and Hu, Jilin and Guo, Shengnan and Yang, Bin and Lin, Youfang and Jensen, Christian S.},
series = {{SIGMOD} '23},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3617337},
url = {https://dl.acm.org/doi/10.1145/3617337},
year = {2023}
}
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,389 | TFB: Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methods | 2024 | VLDB | 7.4394209e-05 |
| 10,760 | RLER-TTE: An Efficient and Effective Framework for En Route Travel Time Estimation with Reinforcement Learning | 2025 | SIGMOD | 5.0723324e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 4 of 4 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 973 | Path Oracles for Spatial Networks | 2009 | VLDB | 0.00012848337 |
| 3,362 | Effective Travel Time Estimation: When Historical Trajectories over Road Networks Matter | 2020 | SIGMOD | 7.4661511e-05 |
| 3,712 | Anytime Stochastic Routing with Hybrid Learning | 2020 | VLDB | 7.163701e-05 |
| 7,388 | DeepTEA: Effective and Efficient Online Time-dependent Trajectory Outlier Detection | 2022 | VLDB | 5.6112677e-05 |
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