ML Anthology

DeepLanes: End-to-End Lane Position Estimation Using Deep Neural Networks

Alexandru Gurghian, Tejaswi Koduri, Smita V. Bailur, Kyle J. Carey, Vidya N. Murali
CVPRW 2016 pp. 38-45
doi:10.1109/CVPRW.2016.12 /cvprw/2016/gurghian2016cvprw-deeplanes/

Abstract

Camera-based lane detection algorithms are one of the key enablers for many semi-autonomous and fully-autonomous systems, ranging from lane keep assist to level-5 automated vehicles. Positioning a vehicle between lane boundaries is the core navigational aspect of a self-driving car. Even though this should be trivial, given the clarity of lane markings on most standard roadway systems, the process is typically mired with tedious pre-processing and computational effort. We present an approach to estimate lane positions directly using a deep neural network that operates on images from laterally-mounted down-facing cameras. To create a diverse training set, we present a method to generate semi-artificial images. Besides the ability to distinguish whether there is a lane-marker present or not, the network is able to estimate the position of a lane marker with sub-centimeter accuracy at an average of 100 frames/s on an embedded automotive platform, requiring no pre-or post-processing. This system can be used not only to estimate lane position for navigation, but also provide an efficient way to validate the robustness of driver-assist features which depend on lane information.

CVPRW Semantic Scholar

Cite

Text

Gurghian et al. "DeepLanes: End-to-End Lane Position Estimation Using Deep Neural Networks." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2016. doi:10.1109/CVPRW.2016.12

Markdown

[Gurghian et al. "DeepLanes: End-to-End Lane Position Estimation Using Deep Neural Networks." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2016.](https://mlanthology.org/cvprw/2016/gurghian2016cvprw-deeplanes/) doi:10.1109/CVPRW.2016.12

BibTeX

@inproceedings{gurghian2016cvprw-deeplanes,
  title     = {{DeepLanes: End-to-End Lane Position Estimation Using Deep Neural Networks}},
  author    = {Gurghian, Alexandru and Koduri, Tejaswi and Bailur, Smita V. and Carey, Kyle J. and Murali, Vidya N.},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2016},
  pages     = {38-45},
  doi       = {10.1109/CVPRW.2016.12},
  url       = {https://mlanthology.org/cvprw/2016/gurghian2016cvprw-deeplanes/}
}