@inproceedings{e420c7569ed7462d8db5ec11f84318e1,
title = "Rating of Take-Over Performance in Conditionally Automated Driving Using an Expert-Rating System",
abstract = "Conditionally Automated Driving could be the next step towards fully automated driving. In this level of automation, the human driver represents the fallback instance and has to be able to regain control of the vehicle if requested. This transition process is currently in focus of human factors research. In previous studies, take-over performance was rated by using data concerning reaction times and quantitative data measuring the quality of the drivers{\textquoteright} input. One disadvantage of this method is that all aspects of the take-over process are considered separately and not the take-over as a whole event. In the current study, a new method for rating of take-over performance was used. The expert rating system TOC [1] was used to rate take-over performance of N = 66 subjects in a driving simulator study. Two different non-driving related tasks (NDRTs) were used to affect fatigue. Results suggest, that take-over performance was poor, independent of NDRTs.",
keywords = "Conditional driving automation, Driving simulation, Expert rating, Human factors, Take-Over performance",
author = "Oliver Jarosch and Klaus Bengler",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG, part of Springer Nature 2019.; AHFE International Conference on Human Factors in Transportation, 2018 ; Conference date: 21-07-2018 Through 25-07-2018",
year = "2019",
doi = "10.1007/978-3-319-93885-1_26",
language = "English",
isbn = "9783319938844",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer Verlag",
pages = "283--294",
editor = "Neville Stanton",
booktitle = "Advances in Human Aspects of Transportation - Proceedings of the AHFE 2018 International Conference on Human Factors in Transportation, 2018",
}