@inproceedings{39e5eafbf23e415ea43cdfce2073d43d,
title = "Hazard detection and cognition for an active driving assistance",
abstract = "The driving assistance technology is an interesting method to increase the safety on the road. By helping the driver to avoid dangerous situations while letting him in charge of the behavior of the vehicle during normal conditions, this kind of system combines both the rapid reactions of an automated system and the human ability to react to unpredictable scenarios. The main demanding aspect of such an assistance is the capability to detect every encountered hazard and to correctly estimate both its nature and location in the space of the moving vehicle. For that purpose, this paper describes an implementation of an active driving assistant on an electric car, as well as the detection process of the dangers, their identifications and location estimations. Moreover to ensure a better detection coverage of the surrounding of the vehicle, a sharing process of the detected hazards between different systems in the controlled car environment is presented.",
keywords = "Driving assistance, Electric vehicle, Information sharing, Location estimation, Steer-by-wire, Stereo camera, Virtual force field",
author = "Baptiste Rouzier and Toshiyuki Murakami",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE. Copyright: Copyright 2017 Elsevier B.V., All rights reserved.; 14th IEEE International Workshop on Advanced Motion Control, AMC 2016 ; Conference date: 22-04-2016 Through 24-04-2016",
year = "2016",
month = jun,
day = "20",
doi = "10.1109/AMC.2016.7496373",
language = "English",
series = "2016 IEEE 14th International Workshop on Advanced Motion Control, AMC 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "340--345",
booktitle = "2016 IEEE 14th International Workshop on Advanced Motion Control, AMC 2016",
}