English

DeepSignals: Predicting Intent of Drivers Through Visual Signals

Computer Vision and Pattern Recognition 2020-11-13 v1 Machine Learning

Abstract

Detecting the intention of drivers is an essential task in self-driving, necessary to anticipate sudden events like lane changes and stops. Turn signals and emergency flashers communicate such intentions, providing seconds of potentially critical reaction time. In this paper, we propose to detect these signals in video sequences by using a deep neural network that reasons about both spatial and temporal information. Our experiments on more than a million frames show high per-frame accuracy in very challenging scenarios.

Keywords

Cite

@article{arxiv.1905.01333,
  title  = {DeepSignals: Predicting Intent of Drivers Through Visual Signals},
  author = {Davi Frossard and Eric Kee and Raquel Urtasun},
  journal= {arXiv preprint arXiv:1905.01333},
  year   = {2020}
}

Comments

To be presented at the IEEE International Conference on Robotics and Automation (ICRA), 2019

R2 v1 2026-06-23T08:56:38.311Z