Probabilistic Traffic Forecasting

Probabilistic Traffic Forecasting is a traffic demand forecasting method that quantifies uncertainty in future traffic conditions by providing probabilistic distributions rather than deterministic point predictions.

120

Publications

6.2K

Citations

392

Authors

189

Institutions

Publications per year

2017–2026

48

Authors

392

  1. AM
    Alexandre M. Bayen

    University of California, Berkeley, United States

    2 publications · 253 citations

    2

    h-index

  2. CF
    Cyril Furtlehner

    Université Paris-Sud, France

    2 publications · 44 citations

    2

    h-index

  3. YQ
    Yan Qi

    Louisiana State University, United States

    2 publications · 244 citations

    2

    h-index

  4. BG
    Banishree Ghosh

    Nanyang Technological University, Singapore

    2 publications · 28 citations

    2

    h-index

  5. JL
    Jean‐Marc Lasgouttes

    Institut national de recherche en sciences et technologies du numérique, France

    2 publications · 44 citations

    2

    h-index

1–5 of 392

Venues

  1. 11

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  2. 11

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  3. 4

    h-index

  4. Transportation Science

    3 publications · 398 citations

    3

    h-index

  5. Knowledge-Based Systems

    2 publications · 113 citations

    2

    h-index

1–5