Mapping the Dream: Designing Optimal E-Bike Routes in Valparaíso, Chile, Using a Multicriteria Analysis and an Experimental Study
ISPRS International Journal of Geo-Information,
Journal Year:
2025,
Volume and Issue:
14(1), P. 38 - 38
Published: Jan. 20, 2025
The
city
of
Valparaíso,
Chile,
faces
significant
mobility
challenges
due
to
its
steep
slopes,
complex
urban
infrastructure,
and
socioeconomic
conditions.
In
this
direction,
study
explores
the
potential
promotion
E-bike
uses
by
identifying
optimal
routes
that
connect
metro
stations
strategic
hilltop
streets
in
city.
A
hybrid
methodology
combining
a
multicriteria
GIS-based
analysis
an
experimental
was
used
evaluate
possibility
increasing
power
limitations
for
non-motorized
Chile.
Fifteen
were
assessed
based
on
criteria
including
slope,
traffic
safety,
directionality,
intersections,
travel
distance.
results
indicate
such
as
Cumming
from
Puerto
Bellavista
stand
out
most
viable
e-bike
use
given
their
favorable
characteristics.
revealed
higher-powered
E-bikes
(500
W
750
W)
would
be
more
able
overcome
slopes
with
average
speed
5.36
km/h
9.52
10.88%
slope.
These
findings
challenge
current
regulatory
limit
250
vehicles
highlighting
benefits
limits
enhance
sustainable
hilly
contexts
country.
This
highlights
need
adapt
policies
unique
topographical
conditions
each
Future
research
should
build
upon
studies,
develop
specific
street-scale
analyses
using
audit
methods,
incorporate
climate-related
variables,
economic
viability
infrastructure.
Addressing
these
aspects
could
position
Valparaíso
leading
example
cities
facing
comparable
challenges.
Language: Английский
Analyzing Public Transport Wait Times and Identifying the Most Affected Users in the Metropolitan Area of Valparaíso, Chile
Applied Sciences,
Journal Year:
2025,
Volume and Issue:
15(11), P. 5969 - 5969
Published: May 26, 2025
Public
transportation
wait
times
are
a
crucial
factor
influencing
users’
perception
of
the
system’s
efficiency,
their
satisfaction,
and
willingness
to
continue
using
these
services.
This
study
analyzes
long
in
public
identifies
most
affected
users
Metropolitan
Area
Valparaíso,
Chile.
Using
data
from
Gran
Valparaíso
Mobility
Transportation
Survey
conducted
by
Planning
Secretariat
(SECTRA)
2014,
only
trips
were
selected,
resulting
dataset
17,951
records.
Exploratory
analysis
techniques
Artificial
Intelligence
algorithms,
such
as
DBSCAN
clustering,
applied,
well
Moran’s
Index
for
spatial
autocorrelation,
order
identify
patterns
groups
experiencing
prolonged
times.
The
results
show
that
certain
demographic
specific
geographic
areas
face
longer
times,
negatively
impacting
equity
accessibility
within
system.
provides
insights
improving
planning
identifying
user
experience
extended
which
can
guide
decisions
enhance
satisfaction
promote
use
transportation.
Language: Английский
Nonlinear and Threshold Effects on Station-Level Ridership: Insights from Disproportionate Weekday-to-Weekend Impacts
ISPRS International Journal of Geo-Information,
Journal Year:
2024,
Volume and Issue:
13(10), P. 365 - 365
Published: Oct. 17, 2024
Station-level
ridership
is
an
important
indicator
for
understanding
the
relationship
between
land
use
and
rail
transit,
which
crucial
building
more
sustainable
urban
mobility
systems.
However,
nonlinear
effects
of
built
environment
on
metro
ridership,
particularly
concerning
temporal
heterogeneity,
have
not
been
adequately
explained.
To
address
this
gap,
study
proposes
a
versatile
methodology
that
employs
eXtreme
gradient
boosting
(XGBoost)
tree
to
analyze
factors
station-level
variations
compares
these
results
with
those
multiple
regression
model.
In
contrast
conventional
feature
interpretation
methods,
utilized
Shapley
additive
explanations
(SHAP)
detail
each
factor
across
dimensions
(weekdays
weekends).
Using
Shanghai
as
case
study,
findings
confirmed
presence
complex
threshold
land-use,
transportation,
station-type
in
association.
The
“Commercial
POI”
represents
most
significant
influence
changes
both
weekday
weekend
models;
“Public
Facility
Station”
plays
role
increasing
passenger
flow
model,
but
it
shows
opposite
effect
change
This
highlights
importance
explainable
machine
learning
methods
comprehending
influences
various
ridership.
Language: Английский
Incident Analysis in Micromobility Spaces at Metro Stations: A Case Study in Valparaíso, Chile
Sustainability,
Journal Year:
2024,
Volume and Issue:
16(23), P. 10483 - 10483
Published: Nov. 29, 2024
This
study
analyzes
passenger
incidents
in
metro
stations
and
their
relationship
with
safety
Valparaiso,
Chile.
The
primary
aim
is
to
examine
how
factors
such
as
station
design,
flow,
weather
conditions
influence
the
frequency
types
of
various
micromobility
spaces
within
stations.
A
comprehensive
data
analysis
was
conducted
using
records
from
Valparaiso
Metro
between
2022
2023.
During
this
period,
approximately
500
were
documented,
providing
a
substantial
dataset
for
identifying
incident
patterns
correlations
contributing
factors.
revealed
that
are
significantly
influenced
by
peak-hour
weekdays.
platform–train
interface
emerged
most
complex
space
occurrences.
Specifically,
found
crowded
inside
trains
during
morning
evening
rush
hours
contribute
substantially
incidents.
In
other
spaces,
closely
linked
type
presence
stair
access.
Conversely,
designed
more
accessible
features
appeared
have
fewer
Future
studies
will
expand
on
framework
incorporating
additional
analyzing
new
develop
understanding
dynamics.
Language: Английский