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