Long-term Traffic Forecasting

Long-Term Traffic Forecasting is a traffic demand forecasting method that predicts traffic conditions over extended temporal horizons, typically ranging from several hours to multiple days or weeks, distinguishing itself from short- or medium-term forecasting by its focus on capturing macroscopic patterns, trends, and structural changes in transportation networks over time.

116

Publications

10.8K

Citations

414

Authors

179

Institutions

Publications per year

2017–2026

78

Authors

414

  1. RL
    Runmei Li

    Beijing Jiaotong University, China

    3 publications · 167 citations

    3

    h-index

  2. BD
    Bowen Du

    Beihang University, China

    2 publications · 282 citations

    2

    h-index

  3. DG
    Dominique Guégan

    Université Paris 1 Panthéon-Sorbonne, France

    2 publications · 82 citations

    2

    h-index

  4. YW
    Yinhai Wang

    University of Washington, United States

    2 publications · 2.3K citations

    2

    h-index

  5. CC
    Chi-Yin Chow

    City University of Hong Kong, Hong Kong SAR China

    2 publications · 155 citations

    2

    h-index

1–5 of 414

Venues

  1. 10

    h-index

  2. arXiv (Cornell University)

    Repository · 5 publications · 1K citations

    5

    h-index

  3. IEEE Access

    5 publications · 226 citations

    5

    h-index

  4. 4

    h-index

  5. Sensors

    4 publications · 854 citations

    4

    h-index

1–5