Corpus ID: 215786327

Where can I drive? Deep Ego-Corridor Estimation for Robust Automated Driving

@article{Michalke2020WhereCI,
  title={Where can I drive? Deep Ego-Corridor Estimation for Robust Automated Driving},
  author={T. Michalke and Colin W{\"u}st and Di Feng and C. Gl{\"a}ser and Maxim Dolgov and Fabian Timm},
  journal={ArXiv},
  year={2020},
  volume={abs/2004.07639}
}
Lane detection is an essential part of the perception module of any automated driving (AD) or advanced driver assistance system (ADAS). So far, model-driven approaches for the detection of lane markings proved sufficient. More recently, however data-driven approaches have been proposed that show superior results. These deep learning approaches typically propose a classification of the free-space using for example semantic segmentation. While these examples focus and optimize on unmarked inner… Expand

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