Autonomous Car Chasing
Abstract
We developed an autonomous driving system that can chase another vehicle using only images from a single RGB camera. At the core of the system is a novel dual-task convolutional neural network simultaneously performing object detection as well as coarse semantic segmentation. The system was firstly tested in CARLA simulations. We created a new challenging publicly available CARLA Car Chasing Dataset collected by manually driving the chased car. Using the dataset, we showed that the system that uses the semantic segmentation was able to chase the pursued car on average 16% longer than other versions of the system. Finally, we integrated the system into a sub-scale vehicle platform built on a high-speed RC car and demonstrated its capabilities by autonomously chasing another RC car.
Cite
Text
Jahoda et al. "Autonomous Car Chasing." European Conference on Computer Vision Workshops, 2020. doi:10.1007/978-3-030-66823-5_20Markdown
[Jahoda et al. "Autonomous Car Chasing." European Conference on Computer Vision Workshops, 2020.](https://mlanthology.org/eccvw/2020/jahoda2020eccvw-autonomous/) doi:10.1007/978-3-030-66823-5_20BibTeX
@inproceedings{jahoda2020eccvw-autonomous,
title = {{Autonomous Car Chasing}},
author = {Jahoda, Pavel and Cech, Jan and Matas, Jiri},
booktitle = {European Conference on Computer Vision Workshops},
year = {2020},
pages = {337-352},
doi = {10.1007/978-3-030-66823-5_20},
url = {https://mlanthology.org/eccvw/2020/jahoda2020eccvw-autonomous/}
}