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Should my vehicle drive as I do? A methodology to determine drivers‘ preference for automated driving styles.

Käthner, David and Griesche, Stefan (2017) Should my vehicle drive as I do? A methodology to determine drivers‘ preference for automated driving styles. TeaP 2017, 26.-29.03. 2017, Dresden.

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Abstract

With automated driving being on the cusp of wide spread market introduction (Rivera & van der Meulen, 2014), Human Factors aspect of design and evaluation of the exact behaviour of automated vehicles gains crucial importance. Safety margins determine an envelope of possible trajectories for the automated vehicle, but as of today, the parameterisation of the vehicle’s behaviour within that envelope to create attractive driving styles has has not received wide spread attention yet (Scherer et al., 2015). However, for acceptance of automated driving functions, deemed critical to deliver the promised reduction in accident numbers, it is essential to design automated driving styles that win end users over to activate them on public roads. In two consecutive studies we investigated how to measure preferences for automated driving styles, whether or not drivers prefer being driven similar to their own driving, or if at least default styles can be created that a majority of the users enjoy. In a first study 43 subjects drove in three scenarios on a two-lane motorway in a motion-based driving simulator. Users were instructed to drive at 120 km/h, forcing them to overtake slower vehicles on the right lane. The scenarios were varied regarding the presence and behaviour of faster cars on the left lane, compelling subjects to decide on timing and execution of overtaking manoeuvres. Based on the data from this study, four prototypical driving styles were extracted, using a multivariate time-series clustering algorithm (Griesche et al., 2014). In a second study, 35 subjects from study 1 rated the attractiveness of the prototypical driving styles gained from that study, in addition to their own style. Using a Best-Worst-Scaling technique, preferences for either one of the prototypical driving styles or their own style could be measured. The results indicate that i) many but not all subjects do like their own styles, but not in every situation, and ii) certain styles exist which are preferred by the great majority of the users.

Item URL in elib:https://elib.dlr.de/106517/
Document Type:Conference or Workshop Item (Speech)
Title:Should my vehicle drive as I do? A methodology to determine drivers‘ preference for automated driving styles.
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Käthner, Daviddavid.kaethner (at) dlr.deUNSPECIFIED
Griesche, StefanStefan.Griesche (at) dlr.deUNSPECIFIED
Date:March 2017
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Published
Keywords:driver modelling, automated driving, driving style, time series clustering, driving comfort
Event Title:TeaP 2017
Event Location:Dresden
Event Type:international Conference
Event Dates:26.-29.03. 2017
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Terrestrial Vehicles (old)
DLR - Research area:Transport
DLR - Program:V BF - Bodengebundene Fahrzeuge
DLR - Research theme (Project):V - Fahrzeugintelligenz (old)
Location: Braunschweig
Institutes and Institutions:Institute of Transportation Systems
Deposited By: Käthner, David
Deposited On:02 May 2017 10:49
Last Modified:31 Jul 2019 20:03

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