An Open Collaborative Research
project in Zurich is using algorithmic technology to automate train movement
and identify impediments to smooth, timely train travel.
Project Leader, Transportation
& Operations Research
Simulated scenarios have an
obvious advantage over real world environments: When the Law of Unintended
Consequences strikes, nobody gets hurt. Nowhere is this more true than in
the railroad industry where a disabled train can spark a cascade of dispatching
problems. To help create a more efficient railway system, a team of IBM
researchers is working on a smarter transportation project that will help the
industry optimize train movement across a nation's entire railway system.
Transportation planners compared
two basic mitigation strategies: Building new railway infrastructure versus
managing existing networks through smarter transportation solutions, such as
algorithms. They asked a key question: What is the best way to evaluate train
activity and metrics? The answer: Through simulation.
Modeling networks: an
Modeling train networks is a long-standing engineering challenge. Older train
simulations involved studying track layout to get a fix on the effectiveness of
various signaling systems. Indeed, some railway functions, such as signaling,
are well served by existing physical simulations. The IBM team is using new
algorithmic technology to address other network issues, such as network-wide
dispatching; performance analysis and visualization, and passenger behavior and
other impeding external events.
Dispatching in China
railway optimization efforts are under way in China, where IBM opened a Global Rail
Innovation Center to advance next-gen rail systems.
The IBM team, coordinated by Marco
, project leader for the Transportation
and Operations Research Group
at IBM Research - Zurich, points out that the
team's focus is on the simulation framework's "logical layer," the
interface between the management layer -- which includes a sophisticated train
scheduler -- and the physical layer -- which ultimately mimics the real railway
"Think of that middle logical layer as the place where
data is shoveled back and forth between the other two layers," says
Laumanns, who spoke in January about the evolution of railway scheduling
optimization techniques at IT13 Rail
The day-long symposium drew experts from IT research, industry and government.
At present, a framework does not exist for a coordinated
simulation of a complex railway system, such as the one that crisscrosses
Europe. Only aspects of Europe's railway system have been simulated, including
train runs and simple dispatching rules.
For commuters, an optimized and simulated railway network
would help ensure a more predictable travel experience. For network operators,
such a framework would offer up a system-wide picture of commuter and freight
trains across countries -- and continents. Moreover, it would enable the
seamless integration of existing railway tools.
For IBM -- and for optimization researchers overall -- the
open source project will demonstrate the power of analytics and optimization
science to develop more responsive control systems in high-speed rail and other
Labels: IBM Research - Zurich, railway, simulation, transportation