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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)

Paper ID
6782
Venue
SIGMOD
Year
2023
Pagerank
5.3893532e-05
Overall Rank
8,547 | 41.57%
DOI
10.1145/3617337

Incoming Non-self Citations Over Time

Authors

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}
}

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