Authors:
Mohamed Amir Benloucif, Chouki Sentouh, Jérôme Floris, Philippe Simon, Serge Boverie, Jean-Christophe Popieul
Keywords:
human-machine cooperation, adaptative lane keeping systems, driver distraction
Abstract:
Driver distraction is an important factor of accidents. Not only in manual driving, but the driver state information is also interesting to consider in automated driving systems in order to provide the driver with a suitable assistance level in respect to his evolving needs. The French national project CoCoVeA focus on developing adaptive cooperation strategies with the aim of designing effective human-machine systems for driving assistance. In this framework a preliminary study is conducted in order to investigate the effects of online adjusting the authority level of a lane keeping assist system to match the driver’s distraction state while engaging in a demanding secondary task. The study took place in the SHERPA-lamih driving simulator. A comparison has been made with manual driving. The results showed improvements in the driving performance and an overall acceptance which encourage a more thorough investigation.
Benloucif M.A.; Sentouh C.; Floris J.; Simon P.; Boverie S. and Popieul J.-C. Cooperation between the driver and an automated driving system taking into account the driver’s state In: Proceedings of the Driving Simulation Conference 2016 Europe, Driving Simulation Association, Paris, France, 2016, pp. 133-139
Download .txt file
@inproceedings{Benloucif2016,
title = {Cooperation between the driver and an automated driving system taking into account the driver’s state},
author = {Benloucif, Mohamed Amir and Chouki Sentouh and Jérôme Floris and Philippe Simon and Serge Boverie and Jean-Christophe Popieul},
editor = {Andras Kemeny and Frédéric Merienne and Florent Colombet and Stéphane Espié},
issn = {0769-0266},
year = {2016},
date = {2016-09-07},
booktitle = {Proceedings of the Driving Simulation Conference 2016 Europe},
pages = {133-139},
address = {Paris, France},
organization = {Driving Simulation Association},
abstract = {Driver distraction is an important factor of accidents. Not only in manual driving, but the driver state information is also interesting to consider in automated driving systems in order to provide the driver with a suitable assistance level in respect to his evolving needs. The French national project CoCoVeA focus on developing adaptive cooperation strategies with the aim of designing effective human-machine systems for driving assistance. In this framework a preliminary study is conducted in order to investigate the effects of online adjusting the authority level of a lane keeping assist system to match the driver’s distraction state while engaging in a demanding secondary task. The study took place in the SHERPA-lamih driving simulator. A comparison has been made with manual driving. The results showed improvements in the driving performance and an overall acceptance which encourage a more thorough investigation.},
keywords = {adaptative lane keeping systems, driver distraction, human-machine cooperation},
}
Download .bib file
TY - CONF
TI - Cooperation between the driver and an automated driving system taking into account the driver’s state
AU - Benloucif, Mohamed Amir
AU - Sentouh, Chouki
AU - Floris, Jérôme
AU - Simon, Philippe
AU - Boverie, Serge
AU - Popieul, Jean-Christophe
C1 - Paris, France
C3 - Proceedings of the Driving Simulation Conference 2016 Europe
DA - 2016/09/07
PY - 2016
SP - 133
EP - 139
LA - en-US
PB - Driving Simulation Association
SN - 0769-0266
L2 - https://proceedings.driving-simulation.org/proceeding/dsc-2016/cooperation-between-the-driver-and-an-automated-driving-system-taking-into-account-the-drivers-state
ER -
Download .ris file
Cite this article
Terms and Conditions for Downloading Driving Simulation Proceedings papers:
By downloading a scientific paper from proceedings.driving-simulation.org, you agree to the following terms and conditions:
- Personal Use Only:
The scientific paper provided on this website is solely for personal, educational, and non-commercial use. You may download and use the paper for your own reference and research purposes only.
- No Reproduction or Distribution:
You may not reproduce, distribute, transmit, publish, or otherwise make the paper available to any third party in any form, whether for commercial or non-commercial purposes, without the express written consent of the Driving Simulation Association.
- Copyright and Ownership:
The scientific paper is protected by copyright laws and is the intellectual property of the respective authors and publishers. All rights not expressly granted herein are reserved.
- Citation and Attribution:
If you use the scientific paper for research, presentations, or any other non-commercial purposes, you must provide appropriate citation and attribution to the original authors as per academic standards.
- No Modification:
You may not modify, alter, or adapt the content of the scientific paper in any way.
- Disclaimer:
The Driving Simulation Association makes no representations or warranties regarding the accuracy, completeness, or suitability of the scientific paper for any particular purpose. The paper is provided as-is, without any warranties, express or implied. The Driving Simulation Association reserves the right to terminate or restrict access to the scientific paper at any time and without notice.