Startup Proposal: Intelligent Traffic Signals
We've seen much activity in transportation lately; electric cars,
self-driving cars, ride sharing. But none of these addresses
traffic congestion, which is, I think, a bigger problem.
Traffic signals have always run timed sequences, where the timings
of each step are set up 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 a boulevard
with sychronized lights with offset timings. (They call that
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 with
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
The possibilities are enormous. I'll describe the setup:
"Nest for Traffic Signals": Any intersection could operate
more efficiently by recognizing traffic patterns and dynamically
adjusting the timing to optimize for traffic throughput (or any
metric) as conditions change. Municipal traffic centers would no
longer need to deal with the low level issues such as the timings
and offsets of individual signals, but instead describe the
overall goals, metrics, algorithms, street topology and note
special cases (holidays, parades, events, construction,
emergencies, etc.). Powerful intelligent traffic control would be
available to all towns and cities without a large investment.
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 phase 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. The
computational task increases with the number of units, but more
processors are crunching on it.
Map Data: Include the knowledge of local street topology
and capacity in these decisions. If there is a congested area,
adjust the timing to encourage alternate routes around it.
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.
Adaptive Timed Lights: 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
everywhere 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). An optimal
self-contained system might include a Lidar sensor mounted on the
underside of the traffic signal.
Choose Your Metric: The performance metric can be
arbitrarily customized. "Optimize for exhaust emissions here,
but optimize for traffic throughput over here, and minimize
traffic down there."
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 and data would be run on a separate
processor independant of the signal timing processor, with a
limited protocol between them. 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
Plug-In: The product will be delivered as replacement
plug-in controllers for current traffic signals.
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.
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 would be a major project and would probably require a staff of
over 100 including experts in multiple disciplines (electrical
engineering, software engineering, simulation, artificial
intelligence, civil engineering, traffic engineers, regulatory,
etc.) and venture funding of around $50 million. It's doable right
now, no new technology needs to be developed. The market, world
wide, seems to be somewhere around $50 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