Technology Profile |
The staggering cost
of inaccurate data
plans where signal splits (i.e. | Need to know
072 Traffic Technology International March/April 2020
www.TrafficTechnologyToday.com
x(24*3600/T)xP vehicle-seconds
per day = (ExFxTx24xP)/3600
vehicle-hours per day.
If, for example, the actual
flow is undercounted by 10% (E
= 0.1), T = 100 sec, the nominal
flow F is 3,000 vehicles/hour,
and P is 25%, then the extra
delay is 50 vehicle-hours per
day. At $20 per vehicle-hour this
is equivalent to $1,000 per day.
So the decision to choose a
technology that is, say, $5K per
intersection cheaper but 10%
less accurate ends up costing the
community a staggering $365K
per year in lost productivity.
This simple analysis assumes
a fixed time signal plan. If the
signal is adaptive, the cost of
inaccuracy will be even larger.
Similar analysis for other
applications like actuated
signals, ramp metering, active
lane management or dynamic
In the 1990’s, Dr. Pravin Varaiya,
a distinguished professor at
the University of California at
Berkeley, was working on some
exciting developments in the
field of traffic analytics when
he realized that the prerequisite
for everything envisioned by
the industry was a level of data
accuracy very rare in the
existing systems deployed
globally. This was the impetus
for the development of a
wireless detection platform that
has leveraged recent progress
in ultra-low-power sensing
and wireless chips to deliver
the required level of accuracy
and reliability.
Evaluating detection options
The traffic industry today has
a broad choice of competing
technologies for detection
and data collection including
inductive loops, wireless
sensors, video, radar, tubes and
probe vehicle data, each with its
advantages and limitations; as
no single technology can claim
to be the best answer for all
applications. However, there is
general agreement that for realtime
data applications, inpavement
solutions like wireless
sensors and inductive loops are
more accurate, while video and
radar are less intrusive but
significantly less accurate.
When choosing a technology,
practitioners are faced with the
following question: How
accurate does a solution have
to be to meet the requirements
of my application, and how
much of a cost premium should
that accuracy command? In
other words, what is the cost
of inaccurate data? As we show
in the following example, that
cost can be surprisingly high
if the data is used for timing
traffic signals.
Suppose a traffic signal
controller runs on fixed time
The benefits of wireless
sensors over inductive
loop technology
> Wireless sensors save
installation time and
maintenance costs over
inductive loops.
> Minimal lane closures are
required and is safer for
workers on the road
> Roadways are not
damaged by sensors and
detection is not destroyed
by resurfacing.
division of cycle time into
durations for each phase) are
computed from vehicle counts
or flow estimates. Suppose also
that the estimated flow in one
phase is in error by E, that is, the
actual flow is (1+E)xF, where F
is the estimated flow in vehicles
per hour. If the intersection is
functioning at capacity (i.e.
cycle time just accommodates
the total traffic), then on average
the affected phase will result in
ExFxT/3600 vehicles being
queued for each saturated cycle,
where T is the cycle time in
seconds. These queued vehicles
each will wait an additional T
seconds. The result is an extra
delay of ExFxT2/3600 vehicleseconds
per saturated cycle.
If P percent of the cycles are
saturated then the daily extra
delay is: (ExFxT2/3600)
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