IBM and Telvent creating smarter traffic solutions for smaller cities
By Anthony Capkun
December 20, 2010
Telvent and IBM aim to develop smarter traffic solutions that are “affordable and customized for small cities, university and government campuses and business districts”. Taking advantage of predictive analytics and real-time information from road sensors allows agencies to be more proactive in dealing with traffic and mobility issues, say the partners.
The solution will apply IBM’s analytics and Telvent’s traffic management expertise to give small urban areas visibility for better traffic control and improving congestion.
“Real-time visibility across an entire transportation network is key to
better traffic management regardless of the size of the area or
population,” said Ignacio Gonzalez, Telvent CEO. “We will be combining
our expertise to give small urban areas transportation operators a
cost-effective way to manage the unique mobility issues that they face,
helping them improve operational performance, get more capacity out of
their existing transportation networks and improving travelers’
The solution can integrate and analyze data traffic control, road
sensors, bus schedules, real-time GPS location, and so forth. For
example, small cities could tap data from GPS devices in sensors
embedded in the roadway. They can analyze the information with
sophisticated algorithms to predict traffic jams around a special event
or large construction project before they happen. By predicting where a
traffic jams will be in, say, an hour, drivers could be automatically
notified ahead of ahead of time, multiple alternate routes could be
suggested and public transportation schedules could be shifted to better
A large university would be able to anticipate and plan around local
constraints on their traffic network like traffic incidents, a football
game or unexpected loss of capacity by adjusting bus scheduling, parking
information, readjusting traffic signals or rerouting traffic flow.
Also, cities can use a wireless system that monitors the availability of
“Whether it is suburban sprawl, corridors with a number of businesses
located close together or the limited routes across a university campus,
existing infrastructure was not designed to handle the reality of
traffic today,” said Rich Varos, director, Intelligent Transportation
Solutions, IBM. “By combining predictive analytics with the realities of
system constraints, transportation operators of any size can implement
more sustainable traffic planning, improved passenger services and
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