Fu’s team analyzed hours of video
taken at a busy intersection near the
Waterloo campus to measure how
driving behavior changed during
snowstorms.
The metrics they were interested
in included driving and braking
speed and the proximity of vehicles
to one another. These metrics can be
used to calculate two key parameters
important for traffic light timing:
free-flow speed (the speed motorists
would drive at if there was no
congestion) and the saturation flow
rate (the hourly rate of vehicles that
would pass through the lights if they
were always on green).
What they discovered was broadly
in line with expectation – vehicles in
snowstorms go slower and take
longer to stop. They found, for
example, that during a snow event
the saturation flow rate reduced by
up to 25%. He noted a similar
reduction in free-flow speed.
Making models
To understand how traffic light
timings could be adjusted to
accommodate these changes the team
ran computer simulations of the data
using PTV’s Vissim modeling software.
Vissim is a “simulation tool which
maps the entire urban infrastructure,”
says Arjan van Andel, the director of
Above: PTV’s
Vissim modeling
software helped test
the new SPaT
We became interested in how can
we time the signal control so that
it will actually take into account the effect
of weather and the changes in driver
behavior that result
Liping Fu, director, Innovative Transportation System
Solutions Lab, Waterloo University, Ontario
Weather has a big impact
on road travel.
According to figures
from the US Federal
Highways Agency (FHWA) over the
last 10 years 21% of all road traffic
accidents occurred during adverse
weather. Such accidents not only
cause injury and property damage,
they accrue knock-on economic
efficiency losses due to slowdowns
and delays.
Because of these impacts traffic
managers are increasingly looking
at ways to improve the weather
responsiveness of their systems. In
the US, for example, the FHWA has
a road weather management program
that has begun to focus on using
mobile observations and connected
vehicle data to support traffic and
maintenance management.
In Canada, meanwhile,
researchers at Waterloo University in
Ontario have been investigating how
traffic lights in urban centres could
be made more responsive to real-time
weather conditions. In the case of the
Waterloo researchers the main
weather condition they are interested
in is winter snow and ice.
“In Canada we experience a long
winter so winter transportation is
a big challenge for us,” says project
lead, Liping Fu, a civil and
environmental engineering
professor and director of
Waterloo’s Innovative
Transportation System
Solutions (iTSS) Lab.
“Signal control is the main
infrastructure in traffic
control so we became
interested in how can we
time the signal control so that it will
actually take into account the effect
of weather and the changes in driver
behavior that result.”
25%
The average reduction in
reduction in the saturation
flow rate of traffic during
a snow storm
(Waterloo University)
Weather Responsive Intersections |
026 Traffic Technology International November/December 2019
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