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Small Container, Big Implications

June 15, 2017

I got a chance to railfan in Houston this past May 5th. I was at the east end of UP’s Englewood Yard. I was waiting for a KCS manifest train to clear up so I could photograph a UP train that had an ex-UP SD9043MAC on the point. As the end of the KCS train came into view, I prepared to photograph the DPU.

But something seemed odd as I watched the DPU get closer. As I pressed the shutter release, I was able to see what had struck me as odd: trailing the DPU was a single well car with a red 20′ container. As the unusual end of train passed me, I took a few shots of it and forgot about it, preoccupied with freshly painted NS 7298 on the point of an MNSEW train.

Once I looked at the images, my curiosity was piqued because based on its appearance, this isn’t just any old 20′ container. A bit of research yielded quite the surprise. It’s much more than a container. According to the owner, BW & Corman Technologies, it’s a Corridor Information Modeling, or CIM, railcar.

 These use a high-precision, high-speed scanner called LIDAR, or Light Detection and Ranging, to read the environment around a train, assessing everything from tree branches hanging down that might bump cargo to the condition of the rail infrastructure, Morrison said.

“It’s a sensor that allows us to collect very accurate, precise data points on the railroad,” he said.

LIDAR and technology are areas of expertise brought to the mix by Bartlett & West, while Corman works in nearly every service aspect of the railroad industry except technology, said Korey Colyer, Corman’s vice president of finance and administration.

But collecting millions of data points as a train speeds along at 60 mph creates a software challenge. How do you take data being collected in real-time and make it usable at the railroad’s main office? BW and Corman met that challenge with the development of IRIS, or Integrated Real-Time Intelligence Solution, an exclusive technology that helps railroads make data-driven decisions faster.

“The data is being streamed behind the scenes as the (CIM) car is traveling, traversing down the tract,” Morrison said. “It’s being sent to the web portal, and the railroads have access to the web portal. Approximately 10 minutes after we pass a feature, they’re getting a report on that feature.”

Those features include such things as signal stands and bridges along railways. Those features and the track currently are assessed manually, and it takes two to three weeks for information about problems to reach the railway.

The software, which allows nearly real-time analysis of data being collected as the CIM car speeds down the track, could be a game-changer for railroads and other industries.

Hmmm. LIDAR capturing millions of data points sounds suspiciously like the primary technology utilized in self-driving automobiles. The notion that they’re worried about tree branches bumping the cargo is cute. Indulge my speculation, but you’re looking at a device that’s developing technology to allow for autonomous train operation.

With CAD (computer aided dispatching), Trip-Optimizer, PTC, real-time locomotive diagnostic uploads and now this, would you agree that we’re getting very close to crew-less trains, at least technologically?

Should we?


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