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Towards Crowd-aware Indoor Path Planning

Summary: Introduces indoor crowd-aware fastest-path and least-crowded-path queries over a flow-based indoor crowd model. A time-evolving population estimator and shared exact/approximate graph-search framework enable scalable routing under predicted room populations. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
12513
Venue
VLDB
Year
2021
Pagerank
5.093636e-05
Overall Rank
11,695 | 19.77%
DOI
10.14778/3457390.3457401

Incoming Non-self Citations Over Time

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Authors

BibTeX Citation

@article{liu_vldb21,
        title = {{Towards Crowd-aware Indoor Path Planning}},
        author = {Liu, Tiantian and Li, Huan and Lu, Hua and Cheema, Muhammad Aamir and Shou, Lidan},
        journal = {PVLDB},
        series = {{VLDB} '21},
        volume = {14},
        number = {8},
        pages = {1365--1377},
        doi = {10.14778/3457390.3457401},
        url = {https://doi.org/10.14778/3457390.3457401},
        year = {2021}
}

Incoming Citations (Sorted by Pagerank)

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Rank Citing Paper Year Venue Pagerank
11,568 Continuous Social Distance Monitoring in Indoor Space 2022 VLDB 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

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