Goal-Directed Pedestrian Prediction
Abstract
Recent advances in road safety have lead to a constant decline of injured traffic participants in Europe per year. Still, the number of injured pedestrians remains nearly constant. As a countermeasure, active pedestrian safety is the focus of current research, for which accurate pedestrian prediction is a prerequisite. In this scope, we propose a method for dynamics-and environment-based pedestrian prediction. We introduce the pedestrian's destination as a latent variable and thus convert the prediction problem into a planning problem. The planning is executed based on the current dynamics of the pedestrian. The distribution over the destinations is modeled using a Particle Filter. Experimental results show a significant improvement over existing approaches such as Kalman Filters.
Cite
Text
Rehder and Kloeden. "Goal-Directed Pedestrian Prediction." IEEE/CVF International Conference on Computer Vision Workshops, 2015. doi:10.1109/ICCVW.2015.28Markdown
[Rehder and Kloeden. "Goal-Directed Pedestrian Prediction." IEEE/CVF International Conference on Computer Vision Workshops, 2015.](https://mlanthology.org/iccvw/2015/rehder2015iccvw-goaldirected/) doi:10.1109/ICCVW.2015.28BibTeX
@inproceedings{rehder2015iccvw-goaldirected,
title = {{Goal-Directed Pedestrian Prediction}},
author = {Rehder, Eike and Kloeden, Horst},
booktitle = {IEEE/CVF International Conference on Computer Vision Workshops},
year = {2015},
pages = {139-147},
doi = {10.1109/ICCVW.2015.28},
url = {https://mlanthology.org/iccvw/2015/rehder2015iccvw-goaldirected/}
}