Hello everybody, my name is Tobias
Schneider, I'm a Ph.D. student
at the Glasgow School of Art
and a research assistant at the Stuttgart
Media School. And today I'm presenting
you our research, increasing the user
experience in autonomous driving through
different feedback modalities by our team
Sabiha Ghellal, Steve Love and Ansgar
Gerlicher. And this research is part
of the Flexcar Research Project
of the Arena2036 research campus.
We were interested in investigating
the impact of different feedback
modalities on the user experience during
an autonomous ride and thereby unboxing
the black box, making the unknown better
understandable. And we focused
on connecting the areas of human computer
interaction, user experience design
and explainable A.I. And our research
question was: will different single
feedback modalities in the form of light,
audio, visualisation, text and vibration
create a positive user experience
in different autonomous driving
situations? We therefore developed
a virtual reality prototype in Unity.
We specified for different types
of general traffic situations that can
occur, and we derived five different
feedback modalities from current research
for an autonomous ride. Regarding
the driving situations, researchers
and automotive employees came together
for a design workshop at the Arena2036
Research Campus, and we identified four
different general categories of driving
situations. And they can be proactive
and reactive. They can be non-critical
and critical. So for proactive ones,
this means that the autonomous vehicle has
sufficient reaction time for a situation
that does not or does endanger human
health or lives. And for reactive ones,
this means that the autonomous vehicle has
insufficient reaction time for a situation
that does not or does endanger human
health or lives. Regarding the feedback
modalities, due to time constraints
I can't go into too much detail,
but we derived five different ones
from the state of the art research
and they are light, audio, visualisation,
text and vibration, and they all have
different patterns to communicate
information during the different driving
situations. Here you can see
some impressions of our virtual reality
prototype. On top left, you can see
our shuttle. It is based on an existing
one, the Olli. On the top right you can
see a tester taking place in the virtual
reality test. On the bottom left, you can
see our cityscape that we used
for our different driving situations.
On the bottom right you can see three
of the five different feedback modalities
being light, visualisation and text.
We created four VR prototypes for each
situation. So proactive, reactive,
non critical and critical. And every
situation was experienced with all five
feedback modalities and a no feedback
baseline. And the order was shuffled
via Latin Square. And our focus
was on situations where the autonomous
vehicle comes to a stop to solve
a situation. Our study was a mixed method
within subject design study with 22
participants, 12 female, 10 male
and an average age of 28.36 years. The 22
participants experienced all different
autonomous driving situations in virtual
reality and the different feedback
modalities, and they were asked to think
aloud during the test. Afterwards,
they had to fill out the user experience
questionnaire short and conducted
an unstructured interview. And after that,
we asked them to rate the different
feedback modalities. Regarding the results
of the user experience questionnaire short
and the think aloud, light
and visualisation were able to create
a significantly increased user experience
compared to the no-feedback baseline.
And 18 testers said that light
was perceived as useful
and understandable. However, 12 of them
said that it did have too many gradients,
so it was a bit too complex. 7 testers
said that visualization was perceived as
helpful, and 8 of them said that
it is reassuring to see what
the autonomous vehicle sees. And even
though sound did not create
a significantly better user experience,
it was perceived as very pragmatic,
which is interesting. Regarding
the feedback rating, testers preferred
softer, less intrusive feedback
for proactive situations and a bit more
prominent feedback for reactive
situations. In this case, it was light
and visualisation for proactive and light
and sound for reactive situations. We then
also asked the participants to tell us
their desired feedback modality pairs
and once again softer, less intrusive
feedback was preferred for proactive
situations, and more prominent feedback
was preferred for reactive situations once
again. To conclude, providing live
feedback about driving situations
in the form of visualisation or light
significantly increases the user
experience compared to a no-feedback
baseline. Softer, less intrusive feedback
is preferred for proactive situations,
and more prominent feedback is preferred
for reactive situations. This research
was sponsored by the German Federal
Ministry of Education and Research,
and I once again want to thank my awesome
team, Steve, Sabiha and Ansgar. Thank
you very much.