An Integrated Framework of Routing and Rebalancing for Robotaxi Systems
Опубликована: Янв. 1, 2025
Язык: Английский
Transition toward driverless robotaxi: Role of social anxiety, perceived safety, and travel habit
Transportation Research Part F Traffic Psychology and Behaviour,
Год журнала:
2025,
Номер
109, С. 1402 - 1418
Опубликована: Фев. 1, 2025
Язык: Английский
How to Promote the Adoption of Electric Robotaxis: Understanding the Moderating Role of Inclusive Design on Interactive Features
Sustainability,
Год журнала:
2024,
Номер
16(20), С. 8882 - 8882
Опубликована: Окт. 14, 2024
In
recent
years,
China
has
witnessed
a
growing
trend
in
the
adoption
of
electric
robotaxi
services,
with
an
increasing
number
users
beginning
to
experience
this
emerging
mode
transportation.
However,
enhancing
user
willingness
ride
remains
core
challenge
that
industry
urgently
needs
address.
Our
study
approached
issue
from
perspective
interactive
features,
surveying
880
respondents
and
utilizing
structural
equation
modeling
analyze
preferences.
The
research
findings
indicate
computer-based
entertainment
significant
positive
impact
on
traffic
information
completeness
social
interaction,
large
effect
(β
>
0.5,
p
<
0.05),
it
also
exerts
small
behavioral
intention
0.1,
0.05).
Traffic
interaction
have
medium
0.3,
addition,
we
confirmed
inclusive
design,
gender,
age
moderating
effects.
Understanding
design
behavior
can
help
drive
changes,
creating
more
human–vehicle
environment
for
people
different
abilities,
such
as
those
autism.
reveals
key
factors
influencing
users’
offers
insights
recommendations
development
practical
application
features
robotaxis.
Язык: Английский
A Note on Quantifying and Refining Platoon Intensity in Mixed Traffic Environments
Опубликована: Янв. 1, 2024
Язык: Английский
Exploring influential factors of fleet and parking management in shared autonomous vehicle systems: An agent-based simulation framework
Опубликована: Янв. 1, 2024
Язык: Английский
Promoting Sustainable Transportation: How People Trust and Accept Autonomous Vehicles—Focusing on the Different Levels of Collaboration Between Human Drivers and Artificial Intelligence—An Empirical Study with Partial Least Squares Structural Equation Modeling and Multi-Group Analysis
Sustainability,
Год журнала:
2024,
Номер
17(1), С. 125 - 125
Опубликована: Дек. 27, 2024
Despite
the
advancement
in
autonomous
vehicles,
public
trust
and
acceptance
are
crucial
for
AV’s
widespread
adoption.
This
study
examines
how
different
collaboration
levels
between
human
drivers
artificial
intelligence
influence
users’
of
AVs.
Using
an
extended
Technology
Acceptance
Model,
this
incorporates
psychological
factors
technological
attitudes
such
as
perceived
safety,
risk,
AI
literacy,
technophobia.
Data
collected
from
392
vehicle
owners
across
11
Chinese
cities
were
analyzed
using
Partial
Least
Squares
Structural
Equation
Modeling
Multi-Group
Analysis.
The
findings
reveal
that
at
fully
manual
level,
ease
use
significantly
influences
usefulness,
while
remains
grounded
mechanical
reliability
rather
than
systems.
In
contrast,
assumes
driving
responsibilities
collaborative
automation
levels,
show
literacy
increases
use,
technophobia
decreases
them,
with
these
effects
varying
levels.
As
takes
on
greater
responsibilities,
becomes
less
critical,
increasingly
acceptance.
These
highlight
need
targeted
education
phased
strategies,
offering
guidance
AV
developers
to
address
user
concerns
build
technologies.
By
enhancing
acceptance,
contributes
sustainable
development
by
promoting
safer
roads
enabling
more
efficient,
resource-conscious
transportation
Gradually
integrating
AVs
into
urban
mobility
also
supports
smart
city
initiatives,
fostering
environments.
Язык: Английский