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Detect and React

Distracted drivers in autonomous cars: Do drivers safely detect and react to unexpected warning signals?

Total Cost €


EC-Contrib. €






Project "Detect and React" data sheet

The following table provides information about the project.


Organization address
postcode: 3584 CS

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Netherlands [NL]
 Project website
 Total cost 177˙598 €
 EC max contribution 177˙598 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2015
 Funding Scheme MSCA-IF-EF-RI
 Starting year 2016
 Duration (year-month-day) from 2016-09-01   to  2018-08-31


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    UNIVERSITEIT UTRECHT NL (UTRECHT) coordinator 177˙598.00


 Project objective

Self-driving, or autonomous, cars promise sustained individual mobility while decreasing the risk of accidents due to human error. Their technological development tops the agendas of European governments and car manufacturers. With technology taking centre stage it is easy to overlook the human driver. However, this would be a grave mistake, as autonomous vehicles still require human action. Specifically, the next frontier in autonomous vehicles is a car that controls the vehicle (e.g., steering, acceleration) and monitors the traffic environment, but that can signal a request for human intervention at any time. Little is known about how drivers detect and react to such unexpected signals. Research on lower levels of automation (e.g., cars with cruise control) suggests that reaction times to unexpected signals tend to be slow. It is, however, not clear what causes this slowdown, especially at higher levels of automation. Is this a failure to detect the signal, or a failure to react timely? My research will identify under what conditions participants (fail to) detect and react to unexpected audio intervention signals. I will measure detection using cognitive neuroscience techniques (Event Related Brain Potentials) and reaction using reaction time in a driving simulator. I will use this innovative method to study detection and reaction in three studies that look at three important factors: the level of automation, the level of distraction of the driver, and the driver's impulsivity and tendency to get distracted. The project combines my expertise on driver distraction and multitasking with Utrecht University's expertise on cognitive neuroscience. The results will provide fundamental insights about human behaviour in higher-level automated vehicles before these systems are released on the road. This knowledge will inform the design of safer technology and better policy for autonomous vehicles.


year authors and title journal last update
List of publications.
2018 Remo M.A. van der Heiden, Christian P. Janssen, Stella F. Donker, Chantal L. Merkx
Visual in-car warnings: How fast do drivers respond?
published pages: , ISSN: 1369-8478, DOI: 10.1016/j.trf.2018.02.024
Transportation Research Part F: Traffic Psychology and Behaviour 2019-07-25
2018 Remo M. A. van der Heiden, Christian P. Janssen, Stella F. Donker, Lotte E. S. Hardeman, Keri Mans, J. Leon Kenemans
Susceptibility to audio signals during autonomous driving
published pages: e0201963, ISSN: 1932-6203, DOI: 10.1371/journal.pone.0201963
PLOS ONE 13/8 2019-07-25
2019 Christian P. Janssen, Linda Ng Boyle, Andrew L. Kun, Wendy Ju, Lewis L. Chuang
A Hidden Markov Framework to Capture Human–Machine Interaction in Automated Vehicles
published pages: 1-9, ISSN: 1044-7318, DOI: 10.1080/10447318.2018.1561789
International Journal of Human–Computer Interaction 2019-07-25

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The information about "DETECT AND REACT" are provided by the European Opendata Portal: CORDIS opendata.

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