International Journal of Human-Computer Interaction,
Journal Year:
2024,
Volume and Issue:
unknown, P. 1 - 19
Published: Aug. 30, 2024
The
necessity
of
human
supervision
and
intervention
during
autonomous
driving
has
long
been
a
topic
controversial
discussion.
From
developer's
perspective,
it
is
expected
that
users
will
readily
adapt
to
well-calibrated
systems
(ADS)
due
their
superior
performance
in
dynamic
tasks
(DDT)
compared
conventional
human-driven
vehicles.
However,
when
passengers
experience
an
vehicle
(AV),
there
may
be
adjustment
period
which
they
modify
behavior
accommodate
the
patterns
ADS.
Additionally,
some
might
not
at
all,
highlighting
potential
limitations
current
ADS
development
strategy.
This
work
studies
dynamics
human-automation
interaction
introduces
"objective
method",
employs
Virtual
Reality
(VR)-enabled
simulation
approach
for
in-depth
behavioral
analysis
concerning
riders'
adaptation
driving.
Specifically,
we
examined
how
participants
interacted
with
intervened
Level
4
operating
under
conservative,
moderate,
aggressive
fully
environment.
A
realistic
urban
road
network
was
recreated
VR,
integrated
traffic
microsimulation
generate
various
scenarios.
Twenty-seven
completed
across
different
AV
modes,
behaviors
analyzed
relation
conditions
aggressiveness.
Key
findings
include:
(1)
Participants
showed
higher
intention
intervene
but
lower
actual
rates
modes
moderate
conservative
suggesting
quicker
more
challenging
(2)
Interventions
generally
proved
unnecessary
sometimes
detrimental
overall
full-AV
(3)
Aggressive
significantly
improved
efficiency,
40%
increase
average
travel
speed
53%
reduction
waiting
time.
interventions
posed
greatest
challenge
achieving
optimal
conditions.
research
provides
insights
into
complex
human-AV
adaptation,
offering
valuable
implications
interface
design,
implementation
strategies,
public
acceptance
technologies.
Asia-Pacific Journal of Business Administration,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Feb. 16, 2024
Purpose
The
proliferation
of
smartwatches
in
the
digital
age
has
radically
transformed
health
and
fitness
management,
offering
users
a
multitude
functionalities
that
extend
beyond
mere
physical
activity
tracking.
While
these
modern
wearables
have
empowered
with
real-time
data
personalized
insights,
their
environmental
implications
remain
relatively
unexplored
despite
growing
emphasis
on
sustainability.
To
bridge
this
gap,
study
extends
UTAUT2
model
smartwatch
features
(mobility
availability)
perceived
security
to
understand
drivers
usage
its
consequent
impact
Design/methodology/approach
proposed
theoretical
is
evaluated
based
collected
from
303
using
hybrid
structural
equation
modeling–artificial
neural
network
(SEM-ANN)
approach.
Findings
PLS-SEM
results
supported
features’
effect
performance
effort
expectancy.
also
role
expectancy,
social
influence,
price
value,
habit
usage.
use
was
found
influence
sustainability
significantly.
However,
did
not
support
association
between
facilitating
conditions
hedonic
motivation
use.
ANN
further
complement
outcomes
by
showing
normalized
importance
100%
most
significant
factor
influencing
Originality/value
Theoretically,
research
broadens
introducing
as
external
variables
new
outcome
technology
On
practical
level,
offers
insights
for
various
stakeholders
interested
implications.
SAE International Journal of Connected and Automated Vehicles,
Journal Year:
2025,
Volume and Issue:
8(2)
Published: Feb. 12, 2025
<div>The
introduction
of
autonomous
vehicles
(AVs)
promises
significant
improvements
to
road
safety
and
traffic
congestion.
However,
mixed-autonomy
remains
a
major
challenge
as
AVs
are
ill-suited
cooperate
with
human
drivers
in
complex
scenarios
like
intersection
navigation.
Specifically,
use
social
cooperation
cues
navigate
intersections
while
rely
on
conservative
driving
behaviors
that
can
lead
rear-end
collisions,
frustration
from
other
users,
inefficient
travel.
Using
virtual
simulator,
this
study
investigates
the
factors-informed
model
reduce
AV
reliance
behaviors.
Four
scenarios,
each
involving
left-turning
driver
proceeding
straight,
were
designed
obfuscate
right-of-way.
The
classification
models
trained
predict
future
priority-taking
behavior
driver.
Results
indicate
employing
able
significantly
more
efficiently
without
affecting
or
rider
comfort
when
compared
baseline,
cautious
AV.
Overall,
research
contributes
improved
interactions
provides
evidence
for
importance
between
human-driven
vehicles.</div>
European Journal of Marketing,
Journal Year:
2025,
Volume and Issue:
unknown
Published: April 9, 2025
Purpose
The
rapid
advancement
of
drone
technology
has
opened
up
a
new
frontier
in
package
delivery,
presenting
promising
solution
for
logistics
and
transportation
challenges.
However,
there
remains
significant
gap
identifying
the
public’s
belief
structure
regarding
adoption
this
extreme
contexts,
such
as
natural
disasters
or
remote
areas.
This
study
aims
to
fill
research
by
investigating
public
beliefs,
emotions
sentiments
towards
deliveries
these
high-risk
scenarios,
where
traditional
delivery
methods
are
often
impractical
unavailable.
Design/methodology/approach
Using
big
data
approach,
authors
applied
machine
learning
scrape
comments
made
social
media
users
on
recent
popular
posts
videos
related
from
Reddit
YouTube.
cleaning
process
narrowed
down
6,403
2,337,
which
were
then
analysed
using
thematic,
emotion
sentiment
analysis
techniques.
Findings
thematic
revealed
five
key
themes
structure:
safety
security
concerns,
scepticism
distrust,
ethical
support
innovation
efficiency
concerns
about
practicality
feasibility.
Sentiment
showed
predominantly
negative
outlook
(53%),
with
confusion
(19.32%)
disappointment
(14.26%)
being
most
prevalent
emotions.
positive
(45%)
curiosity
(9.08%)
approval
(4.51%)
indicate
cautious
optimism
interest
potential
benefits
deliveries.
Research
limitations/implications
Future
should
expand
sources
include
Twitter,
Facebook
Instagram
broader
insights.
Differentiating
between
e.g.
disasters,
pandemics
conflict
zones,
can
reveal
varying
perceptions.
Investigating
how
influence
actual
behaviours
through
longitudinal
designs
field
experiments
is
essential.
Developing
theoretical
models
that
integrate
unique
factors
like
implications
existing
frameworks
will
enhance
understanding.
In
addition,
large-scale
quantitative
surveys
needed
generalise
findings
across
different
populations
contexts.
Practical
have
practical
policymakers,
developers
marketers.
Addressing
safety,
while
highlighting
help
build
trust
acceptance.
Transparent
communication
robust
regulatory
essential
successful
systems.
Originality/value
To
best
authors’
knowledge,
one
first
systematically
analyse
discussions
It
extends
Unified
Theory
Acceptance
Use
Technology
2
Diffusion
Innovations
theories,
providing
fresh
insights
into
influencing
acceptance
technologies.
results
offer
valuable
guidance
developing
effective
policies
strategies
systems,
contributing
reinvention
marketing
disruptive
economy.
