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An Integrated Model for User State Detection of Subjective Discomfort in Autonomous Vehicles

Niermann, Dario and Trende, Alexander and Ihme, Klas and Drewitz, Uwe and Hollander, Cornelia and Hartwich, Franziska (2021) An Integrated Model for User State Detection of Subjective Discomfort in Autonomous Vehicles. Vehicles, 3 (4), pp. 764-777. Multidisciplinary Digital Publishing Institute (MDPI). doi: 10.3390/vehicles3040045. ISSN 2624-8921.

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Official URL: https://www.mdpi.com/2624-8921/3/4/45


The quickly rising development of autonomous vehicle technology and increase of (semi-) autonomous vehicles on the road leads to an increased demand for more sophisticated human–machine-cooperation approaches to improve trust and acceptance of these new systems. In this work, we investigate the feeling of discomfort of human passengers while driving autonomously and the automatic detection of this discomfort with several model approaches, using the combination of different data sources. Based on a driving simulator study , we analyzed the discomfort reports of 50 participants for autonomous inner city driving. We found that perceived discomfort depends on the driving scenario (with discomfort generally peaking in complex situations) and on the passenger (resulting in interindividual differences in reported discomfort extend and duration). Further, we describe three different model approaches on how to predict the passenger discomfort using data from the vehicle’s sensors as well as physiological and behavioral data from the passenger. The model’s precision varies greatly across the approaches, the best approach having a precision of up to 80%. All of our presented model approaches use combinations of linear models and are thus fast, transparent, and safe. Lastly, we analyzed these models using the SHAP method, which enables explaining the models’ discomfort predictions. These explanations are used to infer the importance of our collected features and to create a scenario-based discomfort analysis. Our work demonstrates a novel approach on passenger state modelling with simple, safe, and transparent models and with explainable model predictions, which can be used to adapt the vehicles’ actions to the needs of the passenger.

Item URL in elib:https://elib.dlr.de/145297/
Document Type:Article
Title:An Integrated Model for User State Detection of Subjective Discomfort in Autonomous Vehicles
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Ihme, KlasUNSPECIFIEDhttps://orcid.org/0000-0002-7911-3512UNSPECIFIED
Drewitz, UweUNSPECIFIEDhttps://orcid.org/0000-0002-6542-9698UNSPECIFIED
Date:10 November 2021
Journal or Publication Title:Vehicles
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In ISI Web of Science:Yes
Page Range:pp. 764-777
Publisher:Multidisciplinary Digital Publishing Institute (MDPI)
Keywords:User-focused automation; user monitoring; human computer interaction; human modelling; human-centered computing; HCI models; acceptance of automated vehicles
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Road Transport
DLR - Research area:Transport
DLR - Program:V ST Straßenverkehr
DLR - Research theme (Project):V - NGC KoFiF (old)
Location: Berlin-Adlershof , Braunschweig
Institutes and Institutions:Institute of Transportation Systems > Information Flow Modelling in Mobility Systems, BS
Institute of Transport Research > Leitungsbereich VF
Deposited By: Ihme, Klas
Deposited On:18 Nov 2021 10:27
Last Modified:15 Sep 2023 08:26

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