Sensors,
Journal Year:
2025,
Volume and Issue:
25(6), P. 1660 - 1660
Published: March 7, 2025
This
meta-survey
provides
a
comprehensive
review
of
3D
point
cloud
(PC)
applications
in
remote
sensing
(RS),
essential
datasets
available
for
research
and
development
purposes,
state-of-the-art
compression
methods.
It
offers
exploration
the
diverse
clouds
sensing,
including
specialized
tasks
within
field,
precision
agriculture-focused
applications,
broader
general
uses.
Furthermore,
that
are
commonly
used
remote-sensing-related
surveyed,
urban,
outdoor,
indoor
environment
datasets;
vehicle-related
object
agriculture-related
other
more
datasets.
Due
to
their
importance
practical
this
article
also
surveys
technologies
from
widely
tree-
projection-based
methods
recent
deep
learning
(DL)-based
technologies.
study
synthesizes
insights
previous
reviews
original
identify
emerging
trends,
challenges,
opportunities,
serving
as
valuable
resource
advancing
use
sensing.
IEEE Transactions on Intelligent Vehicles,
Journal Year:
2023,
Volume and Issue:
8(7), P. 3775 - 3780
Published: July 1, 2023
Autonomous
driving
(AD)
and
Cooperative
Driving
Automation
(CDA)
hold
great
promise
for
transforming
mobility.
However,
current
off-the-shelf
AD
or
CDA
platforms
such
as
Autoware,
Apollo,
CARMA,
are
subject
to
gaps
between
simulation
the
real
world
do
not
offer
integrated
pipelines
research,
development,
deployment.
In
this
letter,
we
conceptualize
OpenCDA-ROS,
building
on
strengths
of
an
open-source
framework
OpenCDA
Robot
Operating
System
(ROS),
seamlessly
synthesize
ROS's
real-world
deployment
capabilities
with
OpenCDA's
mature
research
simulation-based
evaluation
fill
aforementioned.
OpenCDA-ROS
will
leverage
advantages
both
ROS
boost
prototyping
critical
features
in
world,
particularly
cooperative
perception,
mapping
digital
twinning,
decision-making
motion
planning,
smart
infrastructure
services.
By
offering
seamless
integration
CDA,
contributes
significantly
advancing
fundamental
testing,
validation,
prototyping,
autonomous
CDA.
Electronics,
Journal Year:
2024,
Volume and Issue:
13(5), P. 885 - 885
Published: Feb. 26, 2024
The
rapid
development
of
vehicle
cooperative
3D
object-detection
technology
has
significantly
improved
the
perception
capabilities
autonomous
driving
systems.
However,
ship
received
limited
research
attention
compared
to
driving,
primarily
due
lack
appropriate
datasets.
To
address
this
gap,
paper
proposes
S2S-sim,
a
novel
dataset.
Ship
navigation
scenarios
were
constructed
using
Unity3D,
and
accurate
models
incorporated
while
simulating
sensor
parameters
real
LiDAR
sensors
collect
data.
dataset
comprises
three
typical
scenarios,
including
ports,
islands,
open
waters,
featuring
common
classes
such
as
container
ships,
bulk
carriers,
cruise
ships.
It
consists
7000
frames
with
96,881
annotated
bounding
boxes.
Leveraging
dataset,
we
assess
performance
mainstream
when
transferred
scenes.
Furthermore,
considering
characteristics
data,
propose
regional
clustering
fusion-based
method.
Experimental
results
demonstrate
that
our
approach
achieves
state-of-the-art
in
object
detection,
indicating
its
suitability
for
perception.
iScience,
Journal Year:
2024,
Volume and Issue:
27(5), P. 109751 - 109751
Published: April 17, 2024
Cooperative
vehicle-infrastructure
system
(CVIS)
is
an
important
part
of
the
intelligent
transport
(ITS).
Autonomous
vehicles
have
potential
to
improve
safety,
efficiency,
and
energy
saving
through
CVIS.
Although
a
few
CVIS
studies
been
conducted
in
transportation
field
recently,
comprehensive
analysis
necessary,
especially
about
how
applied
autonomous
vehicles.
In
this
paper,
we
overview
relevant
architectures
components
After
that,
state-of-the-art
research
applications
are
reviewed
from
perspective
improving
vehicle
saving,
including
scenarios
such
as
straight
road
segments,
intersections,
ramps,
etc.
addition,
datasets
simulators
used
CVIS-related
summarized.
Finally,
challenges
future
directions
discussed
promote
development
provide
inspiration
reference
for
researchers
ITS.
Sensors,
Journal Year:
2025,
Volume and Issue:
25(6), P. 1660 - 1660
Published: March 7, 2025
This
meta-survey
provides
a
comprehensive
review
of
3D
point
cloud
(PC)
applications
in
remote
sensing
(RS),
essential
datasets
available
for
research
and
development
purposes,
state-of-the-art
compression
methods.
It
offers
exploration
the
diverse
clouds
sensing,
including
specialized
tasks
within
field,
precision
agriculture-focused
applications,
broader
general
uses.
Furthermore,
that
are
commonly
used
remote-sensing-related
surveyed,
urban,
outdoor,
indoor
environment
datasets;
vehicle-related
object
agriculture-related
other
more
datasets.
Due
to
their
importance
practical
this
article
also
surveys
technologies
from
widely
tree-
projection-based
methods
recent
deep
learning
(DL)-based
technologies.
study
synthesizes
insights
previous
reviews
original
identify
emerging
trends,
challenges,
opportunities,
serving
as
valuable
resource
advancing
use
sensing.
