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@PHDTHESIS{Vo:795637,
author = {Voß, Gudrun Mechthild},
othercontributors = {Schwalm, Maximilian and Müsseler, Jochen},
title = {{R}egulatives {F}ahrerverhalten und dessen {R}elevanz für
das automatisierte {F}ahren : {A}usarbeitung und
{U}ntersuchung eines {A}rbeitsmodells zu funktionalen
{V}erhaltensanpassungen},
school = {Rheinisch-Westfälische Technische Hochschule Aachen},
type = {Dissertation},
address = {Aachen},
reportid = {RWTH-2020-08467},
pages = {1 Online-Ressource (XXII, 257 Seiten) : Illustrationen,
Diagramme},
year = {2020},
note = {Veröffentlicht auf dem Publikationsserver der RWTH Aachen
University; Dissertation, Rheinisch-Westfälische Technische
Hochschule Aachen, 2020},
abstract = {Individual mobility is a central theme of human societies.
In this context, the car has become the primary means of
transport in which the execution of the driving task already
constitutes a high task load for drivers. Nevertheless, they
often work on non-driving related tasks. Due to the limited
human cognitive resources, this parallel processing of
multiple tasks can lead to driver distraction. Yet, people
are rarely involved in serious accidents relative to the
kilometres driven. Drivers thus seem to have abilities for
the avoidance of accidents. Research in the context of
non-automated driving can support this claim. Studies could
show that drivers - based on their situation awareness -
proactively regulate their (cognitive) resources and shift
them from the non-driving related tasks to the driving task
in case they expect a critical driving situation or driving
performance. Various theoretical models dealt with this
regulative driver behaviour. Based on these, a holistic
working model originates from Schwalm, Voß and Ladwig
(2015; Voß $\&$ Schwalm, 2015). It conceptualises this
regulative driver behaviour as functional behavioural
adaptations. While in non-automated driving drivers are
responsible for the safe execution and monitoring of the
driving task, in automated driving such a permanent
involvement in the driving task is no longer necessary,
depending on the degree of automation. Drivers can work on
non-driving related tasks (from SAE Level 3 on) and
drivers’ situation awareness decreases. However, they are
allowed to intervene into the automated vehicle guidance at
any time or are even required as fall-back option up to a
certain degree of automation (until SAE Level 3). This
combination of a reduced situation awareness and possible
driver interventions in automated driving raises the
question of how drivers guarantee a safe driving performance
in such situations and whether they can make use of
functional behavioural adaptations. This doctoral thesis
deals with this topic. The objectives are (a) the
theory-based and empirical elaboration of selected
components of the working model regarding functional
behavioural adaptations from Schwalm et al. (2015; Voß $\&$
Schwalm, 2015) as theoretical frame of reference of this
doctoral thesis, and (b) the specific investigation of the
availability and characteristics of these in the context of
automated driving. For this purpose, the working model was
detailed theory-based. It was highlighted that the
functional behavioural adaptations in the multitasking
context particularly occur depending on the perception of a
situation and depending on the subjective evaluation of a
driving performance. Following, assumptions were made on how
functional behavioural adaptations work in the context of
automated driving. It was postulated that in case of
takeovers, driver proactively reduce activity in non-driving
related tasks to release cognitive resources, which
subsequently are used for the safe execution of the driving
task. These assumptions were empirically assessed. In a
driving simulation study (study 1), the functional
behavioural adaptations were examined as a function of the
perception of a changing driving situation (takeover from
automated to non-automated driving). According to the
theoretical assumptions, drivers proactively reduced the
processing of a non-driving related task before a takeover,
released cognitive resources, and thus enabled a safe
takeover. The following studies investigated the idea that
such functional behavioural adaptations can also occur in
case of deviations from a subjectively accepted trajectory.
Initially, the construct of a subjectively accepted driving
performance was examined by means of discriminant function
and factor analysis (study 2). Thresholds of such a
subjectively accepted driving performance regarding the
lateral offset as a function of various personal and
situational factors were examined (studies 3 and 4).
Subsequently, studies 5 and 6 investigated the relevance for
action of the thresholds in the multitasking context of
automated driving in a simulator and under real conditions
on a text track. In case the thresholds were exceeded, not
only comfort losses but also the expected functional
behavioural adaptations occurred. After a proactive
reduction of the non-driving related task, drivers often
intervened in the automated vehicle guidance. Some of the
interventions, however, were not optimal or even safety
critical. These insights of the six empirical studies
allowed for conclusions regarding the availability of
functional behavioural adaptations in the context of
automated driving. Furthermore, future research needs were
identified, for example a continued working model validation
or the design of automated systems which support the
functional behavioural adaptations.},
cin = {721220 / 313410},
ddc = {150},
cid = {$I:(DE-82)721220_20140620$ / $I:(DE-82)313410_20140620$},
typ = {PUB:(DE-HGF)11},
doi = {10.18154/RWTH-2020-08467},
url = {https://publications.rwth-aachen.de/record/795637},
}
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