Agent State Estimation

Agent State Estimation is a computational method in traffic prediction that determines the current dynamical condition of a traffic participant by estimating its kinematic and positional attributes from sensor observations, distinguishing itself from broader prediction tasks by focusing exclusively on the instantaneous state rather than future behaviors or intentions.

155

Publications

8.8K

Citations

527

Authors

217

Institutions

Publications per year

2017–2026

90

Authors

527

  1. KS
    Kamil Saigol

    Georgia Institute of Technology, United States

    3 publications · 418 citations

    3

    h-index

  2. XY
    Xinyan Yan

    Institute of Chemical Industry of Forest Products, China

    3 publications · 418 citations

    3

    h-index

  3. DS
    Davide Scaramuzza

    University of Zurich, Switzerland

    3 publications · 260 citations

    3

    h-index

  4. WY
    Wen Yang

    East China University of Science and Technology, China

    3 publications · 175 citations

    3

    h-index

  5. CC
    Ching-An Cheng

    Georgia Institute of Technology, United States

    3 publications · 418 citations

    3

    h-index

1–5 of 527

Venues

  1. arXiv (Cornell University)

    Repository · 9 publications · 487 citations

    9

    h-index

  2. IEEE Transactions on Automatic Control

    7 publications · 588 citations

    7

    h-index

  3. IET Control Theory and Applications

    5 publications · 257 citations

    5

    h-index

  4. IEEE Robotics and Automation Letters

    4 publications · 309 citations

    3

    h-index

  5. 3

    h-index

1–5