Lane Geometry Estimation

Lane Geometry Estimation is a computational method in computer vision that models the spatial configuration and curvature of road lanes from sensor data by fitting geometric primitives—such as polynomials, splines, or parametric curves—to detected lane markings, thereby enabling precise localization and trajectory planning in autonomous driving systems.

121

Publications

4.9K

Citations

379

Authors

154

Institutions

Publications per year

2017–2026

34

Authors

379

  1. AE
    Andreas Eidehall

    Volvo (Sweden), Sweden

    6 publications · 184 citations

    6

    h-index

  2. FG
    Fredrik Gustafsson

    Linköping University, Sweden

    5 publications · 127 citations

    5

    h-index

  3. TN
    Takashi Naito

    Toyota Central Research and Development Laboratories (Japan), Japan

    3 publications · 109 citations

    3

    h-index

  4. RA
    Romuald Aufrère

    Université Clermont Auvergne, France

    3 publications · 126 citations

    3

    h-index

  5. SL
    Sukhan Lee

    Sungkyunkwan University, South Korea

    3 publications · 49 citations

    3

    h-index

1–5 of 379

Venues

  1. 10

    h-index

  2. Autonomous Robots

    2 publications · 162 citations

    2

    h-index

  3. 2

    h-index

  4. Journal of Transportation Engineering

    2 publications · 22 citations

    2

    h-index

  5. IET Intelligent Transport Systems

    2 publications · 33 citations

    2

    h-index

1–5