Project

ADAS&Me

Period
1 September 2016–29 February 2020
Project manager
Anna Anund

ADAS&Me (Adaptive ADAS to support incapacitated drivers Mitigate Effectively risks through tailor made HMI under automation) aims to develop ADAS that incorporate driver / rider state, situational / environmental context and adaptive HMI to automatically hand over different levels of automation and thus ensure safer and more efficient road usage for all vehicle types (conventional and electric car, truck, bus, motorcycle). SAFER’s partner VTI is leading this project and Autoliv is going to test their steering wheel for human monitoring.

Partners: Safer partners: Autoliv, VTI (Anna Anund coordinator). In total there are 30 project partners.

Short facts

Research area
Road user behaviour
Financier(s)
EU
Partners
VTI
Autoliv
Smart Eye
Other EU partners
More information
http://www.adasandm…
Project type
SAFER connected project

Related publications

Towards a Context-Dependent Multi-Buffer Driver Distraction Detection Algorithm

This paper presents initial work on a context-dependent driver distraction detection algorithm called AttenD2.0, which extends the original AttenD algorithm with elements from the Minimum Required Attention (MiRA) theory. Central to the original AttenD

Authors : Christer Ahlström, George Georgoulas, Katja Kircher
Year : 2021
Published in : IEEE Transactions on Intelligent Transportation Systems

Effects of partially automated driving on the development of driver sleepiness

The objective of this study was to compare the development of sleepiness during manual driving versus level 2 partially automated driving, when driving on a motorway in Sweden. The hypothesis was that partially automated driving will lead to higher levels

Authors : Christer Ahlström, Raimondas Zemblys, Herman Jansson, Christian Forsberg, Johan Karlsson, Anna Anund
Year : 2021
Published in : Accident Analysis & Prevention

Stress, fatigue and inattention amongst city bus drivers – an explorative study on real roads within the ADAS&ME project

Knowledge about normal glance behaviour and typical stress and fatigue levels amongst city bus drivers is very sparse. We therefore conducted an exploratory pre-study with 15 participants during an actual shift in real traffic with passengers. The aim was

Authors : Ahlström C., Anund A., Håkansson Kjellman E.
Year : 2018
Published in : Proceedings of the 6th Driver Distraction and Inattention conference, Gothenburg, Sweden

The importance of subject-dependent classification and imbalanced class distributions in driver sleepiness detection in realistic conditions

The first in-depth study on the use of electrocardiogram and electrooculogram for subject-dependent classification in driver sleepiness/fatigue under realistic driving conditions is presented in this work. Since acquisitions in simulated environments may

Authors : Silviera C. S., Cardoso J. S., Lourenco A. R., Ahlström C.
Year : 2018
Published in : IET Intelligent Transport Systems

Collecting end-users needs regarding driver state-based automation in the ADAS&ME project

The EU funded project ADAS&ME (Adaptive ADAS to support incapacitated drivers & Mitigate Effectively risks through tailor made HMI under automation) develops adapted Advanced Driver Assistance Systems. A web based survey was designed to collect the opinion

Authors : Dukic Willstrand T., Anund A., Pereira Cocron M., Griesche S., Strand N., Troberg S., Zanovello L. and Nikolaou S.
Year : 2018
Published in : Proceedings of 7th Transport Research Arena TRA 2018, April 16-19, 2018, Vienna, Austria