@inproceedings{7c50a5c9e72c4d818a4bd6d76debd46c,
title = "Vision-Based Driver Assistance Systems: Survey, Taxonomy and Advances",
abstract = "Vision-based driver assistance systems is one of the rapidly growing research areas of ITS, due to various factors such as the increased level of safety requirements in automotive, computational power in embedded systems, and desire to get closer to autonomous driving. It is a cross disciplinary area encompassing specialised fields like computer vision, machine learning, robotic navigation, embedded systems, automotive electronics and safety critical software. In this paper, we survey the list of vision based advanced driver assistance systems with a consistent terminology and propose a taxonomy. We also propose an abstract model in an attempt to formalize a top-down view of application development to scale towards autonomous driving system.",
keywords = "ADAS, Automotive Vision, Autonomous Driving, Computer Vision, Embedded Vision, Machine Learning",
author = "Jonathan Horgan and Ciaran Hughes and John McDonald and Senthil Yogamani",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 18th IEEE International Conference on Intelligent Transportation Systems, ITSC 2015 ; Conference date: 15-09-2015 Through 18-09-2015",
year = "2015",
month = oct,
day = "30",
doi = "10.1109/ITSC.2015.329",
language = "English",
series = "IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2032--2039",
booktitle = "Proceedings - 2015 IEEE 18th International Conference on Intelligent Transportation Systems",
}