Car Safety Support System on the Base of Data Mining Algorithm
- DOI
- 10.2991/aebmr.k.211118.060How to use a DOI?
- Keywords
- decision making algorithm; decision rules; autonomous driving; ADAS; sustainable transport; EAV model; decision table; machine vision; objects detection; image recognition; road safety
- Abstract
According to the target of the 11th Sustainable Development Goal, to reach sustainability in cities, we have to ensure the transport systems’ safety. Since safety driver assistance systems play a critical role both in averting crashes and reducing the likelihood of serious injury, we suggest a Safety Support System based on machine vision and a data mining algorithm that could be used for application to decision module of fully- or semi-autonomous vehicles. The created system was tested on a simple collection of photos from a Polish two-lane road. The novelty of this system is concluded in our EAV (Entity–Attribute–Value) model based algorithm that, while providing the same level of accuracy, works faster by reducing the number of analyzed attributes.
- Copyright
- © 2021 The Authors. Published by Atlantis Press International B.V.
- Open Access
- This is an open access article under the CC BY-NC license.
Cite this article
TY - CONF AU - Krzysztof Zabinski AU - Ksenia Shubenkova AU - Irina Makarova AU - Beata Zielosko PY - 2021 DA - 2021/11/29 TI - Car Safety Support System on the Base of Data Mining Algorithm BT - Proceedings of the Second Conference on Sustainable Development: Industrial Future of Territories (IFT 2021) PB - Atlantis Press SP - 335 EP - 341 SN - 2352-5428 UR - https://doi.org/10.2991/aebmr.k.211118.060 DO - 10.2991/aebmr.k.211118.060 ID - Zabinski2021 ER -