Interaction-aware Prediction

Interaction-Aware Prediction is a modeling paradigm in traffic participant forecasting that belongs to the class of trajectory prediction methods and is distinguished by its explicit incorporation of dynamic interdependencies and behavioral influences among multiple agents in shared environments.

63

Publications

4.1K

Citations

209

Authors

96

Institutions

Publications per year

2017–2026

54

Authors

209

  1. MT
    Masayoshi Tomizuka

    University of California, Berkeley, United States

    8 publications · 357 citations

    8

    h-index

  2. WZ
    Wei Zhan

    University of California, Berkeley, United States

    4 publications · 216 citations

    4

    h-index

  3. HM
    Hengbo Ma

    University of California, Berkeley, United States

    4 publications · 141 citations

    4

    h-index

  4. JL
    Jiachen Li

    University of California, Berkeley, United States

    4 publications · 141 citations

    4

    h-index

  5. CL
    Chen Lv

    Nanyang Technological University, Singapore

    3 publications · 179 citations

    3

    h-index

1–5 of 209

Venues

  1. 6

    h-index

  2. IEEE Transactions on Intelligent Vehicles

    ITIVBL · 6 publications · 659 citations

    6

    h-index

  3. arXiv (Cornell University)

    Repository · 5 publications · 177 citations

    5

    h-index

  4. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 2 publications · 91 citations

    2

    h-index

  5. Neurocomputing

    2 publications · 256 citations

    2

    h-index

1–5