Traffic Demand Forecasting

Traffic Demand Forecasting is a systematic analytical process within transportation planning that estimates the future volume and spatial distribution of vehicular movements across a highway network based on socioeconomic and land-use projections, travel behavior models, and network characteristics.

1.7K

Publications

83.2K

Citations

5K

Authors

1.3K

Institutions

Publications per year

2017–2026

870

Authors

5K

  1. HS
    Hani S. Mahmassani

    Northwestern University, United States

    12 publications · 636 citations

    11

    h-index

  2. JY
    Jieping Ye

    Arizona State University, United States

    9 publications · 2.9K citations

    9

    h-index

  3. HY
    Hai Yang

    Hong Kong University of Science and Technology, Hong Kong SAR China

    8 publications · 1.3K citations

    8

    h-index

  4. WH
    William H. K. Lam

    Hong Kong Polytechnic University, Hong Kong SAR China

    8 publications · 713 citations

    8

    h-index

  5. CW
    Craig Wanke

    Mitre (United States), United States

    8 publications · 230 citations

    8

    h-index

1–5 of 5K

Venues

  1. 39

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  2. 33

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  3. 32

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  4. 21

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  5. IEEE Access

    31 publications · 1.1K citations

    21

    h-index

1–5