Startup Proposal: Intelligent Traffic Signals
We've seen many exciting developments in transportation lately;
electric cars, self-driving cars, ride sharing. But none of these
addresses traffic congestion, which is, I think, a far more
Traffic signals have always run timed sequences, where the timings
for each step are programmed by traffic engineering professionals.
The more advanced setups have branches triggered by pedestrian
requests or left turn lane sensors, but the steps are still timed.
Traffic signals can be independent, or a number of units can be
under the control of a central computer system, such as with a
boulevard installation with sychronized lights with offset timings.
(The term they use is "progression".)
And we've all been stuck in frustrating traffic situations where the
signals just happened to go the worst possible ways at the worst
What if traffic signals were autonomous intelligent devices, each
with an iPhone-like microprocessor, sensors, and connectivity? What if
they were able to continuously adjust and optimize their timings for
the most efficient possible traffic flow on their own? What if they
could replace the monitoring and controlling functions of municipal
traffic control centers?
More efficient travel with less traffic congestion could likely save
billions of gallons of gasoline and tens of millions of tons of
exhaust emissions each year in the US alone. Less road
construction would be needed as existing roads are used more
efficiently. The possibilities are enormous.
I'll describe the setup:
Immediate Efficiency Improvements:No more pointless waiting
at a signal with zero cross traffic.
"Nest for Traffic Signals": Any intersection could operate
more efficiently by recognizing traffic patterns and dynamically
adjusting the timing ratios and the timing cycle rate to optimize
traffic as conditions change. Powerful intelligent traffic
control would be available to all towns and cities at low cost.
Metrics Instead of Timings: Traffic engineers would no
longer set timings or offsets, but instead set the overall goals,
metrics, and algorithms. Further, the metrics can be arbitrarily
customized; "optimize for exhaust emissions here, but optimize for
traffic throughput over here, and minimize traffic down there."
Working Together: Nearby smart signals can coordinate with
each other to optimize traffic flow with no central computer
involved. Connections to nearby units share data, communicate
needs, and dynamically adjust the timing offsets between the
signals for optimium traffic flow. When there is a congested
area, increase the green time to empty that area out while the
signals feeding the area reduce their green time and encourage
Adaptive Computational Resources: The computational task
increases with the number of interconneted intellegnet traffic
signals, but more processors are crunching on it. And enormous
computational resources are available in the cloud.
Modeling and Prediction: The traffic signals could also use
the networked data to anticipate upcoming traffic situations.
Potential congested areas could be emptied out before they become
Run Experiments: Operate with timings slightly tweaked,
collecting statistical data to find optimal traffic patterns for
each particular intersection. Share the experimental data with
other areas, compile statistics, and become smarter over time.
Boulevard Case: Timed boulevard lights currently require
central control of all the units involved and an assumption of how
quickly the cars can get through. Traffic gets messy if that
assumption isn't met. Intelligent traffic signals could work
together automatically providing synchronization anywhere without
central control, dynamically adjusting the signal phases to
accommodate a wide variation in conditions. Optimum
synchronization could be maintained even with disruptions such as
random pedestrian crossings. Further, intelligent traffic signals
can bridge the gap between boulevard lights managed by the
county/state and local lights managed by the town/city.
Gridlock Conditions (cars stuck within intersections) could
be flagged and efficiently emptied out with a separate algorithm.
Sensors: The system would include an abstraction layer to
accept traffic flow input from any kind of sensors that might be
available (buried loops, video, whatever).
It's a Platform: New parameters, algorithms, simulations,
and software could be uploaded at any time. The system would have
an open API for traffic management algorithms, a new market. So
when some researchers develop an improved or specialized algorithm
it can be uploaded and put to use with measurable results.
Simulation and Lookahead:As an alternative to algorithms,
intelligent traffic signals could perform continuous simulations
fed by data from nearby units and, like a classic computer chess
program, look several moves ahead and choose the best option.
Verifiable: The system could demonstrate results at any
time by reverting to the original signal timings and measuring the
Safe: The alorithms would be run on a separate processor
independant of the signal timing processor, with a limited
protocol between the two. So in the event of a crippling software
bug or Dr. Evil hack, the signal timing processor would just leave
the lights running in the default pattern. (There is also the
standard safety net called the Conflict Monitor Unit that
watches for inappropriate signal conditions and brings the system
down to blinky mode if anything is amiss.)
Extras: Smart traffic signals could provide hooks to assist
driverless cars. A phone app could provide a pedestrian walk
signal at any intersection. Another phone app could charge the
user for faster access through traffic and generate revenue for
Services: All sorts of monitoring, analysis, and support
services could be available by subscription.
A municipality could purchase smart traffic signals over time on a
replacement basis, similar to the switch to LED traffic lights.
Each new traffic signal will improve the performance of nearby
smart traffic signals so there is an incentive to add more. The
most appreciative customers would likely be suburbs with traffic
congestion problems; they could get the advantages of synchronized
lights, and more, without the expense of a central computer system.
There are at least 300,000 signaled intersections in the US.
International sales would be substantial. Cities and counties are
accustomed to spending $50,000 to $500,000 to purchase and install a
traffic signal. Annual revenues would be billions of dollars in
direct sales alone. This could be an enormous business that has a
profoundly positive effect on the environment.
There could be several implementations. One could be a drop-in
replacement for current traffic controller electronics, typically
located in those weatherproof boxes you see at intersections, and
that would interfaces to the existing sensors and lights.
Another possiblity would be an all-in-one traffic light assembly
with a self-contained controller and a Lidar unit mounted on the
bottom. This would have a low installation cost, and the Lidar unit
would be able to monitor traffic very accurately without being an
invasion of privacy.
I'm not seeing evidence of anybody currently doing anything like
this. There is a new development in traffic signals called
"Adaptive Traffic Control"
Adaptive Signal Control Technology), but all implementations so
far seem to be major projects involving a central computer system.
There are some experiments in the references below, certainly, but I
don't see any patents, or solid progress, or any in use, or anybody
approaching it the way I've described here.
In 2013 the city of Los Angeles finished a $400 million project to
sequence all of their 4500 traffic signals from a central computer
facility staffed with traffic engineers.
Times: To Fight Gridlock, Los Angeles Synchronizes Every Red
Light) It doesn't appear to have helped; Los Angeles has the
worst traffic in the world according to a 2017 Inrix study.
This is doable right now; no new technology is necessary, and the
algorithms can be developed over time. The market, world wide,
might to be somewhere around $100 billion.
Zubillaga, et al:
Measuring the Complexity of Self-Organizing Traffic Lights
How AI Turns Traffic Lights Into Intelligent Agents
Design of Intelligent Traffic Light Controller Using Embedded
Carnegie Mellon University:
Smart Traffic Signals
Carnegie Mellon University:
Smart Signals — Pilot Study on Traffic Lights Reduces
Pollution, Traffic Clogs
US Department of Transportation:
Manual on Uniform Traffic Control Devices
Smarter programming of stoplights could improve efficiency of
How smart traffic signals may ease your commute
Choreographing the Dance of Traffic Lights
Ghena, et al:
Green Lights Forever: Analyzing the Security of Traffic Infrastructure
Boston Transportation Department:
The Benefits of Retiming/Rephasing Traffic Signals in the Back Bay