The Real-Time Public Transportation Accelerator
With all the buzz about driverless cars, advances in automated mass transit have gone relatively unnoticed. In 2010, President Obama’s Open Data Initiative sparked the community to share data for the public good. Today, we reap the rewards of open data for public transportation. With autonomous vehicles on the horizon, we’re prepared to manage them.
Google started to support open transit data to support Google Maps in 2010. Eventually, the global transportation industry followed suit. The General Transit Feed Specification (GTFS) standard emerged which allows any participant to share and consume data.
At TIBCO, we took the open data push a step higher by contributing an open “accelerator” to the community. The Real-Time Public Transportation Accelerator is a free fast-start template for transportation system operators.
The snapshot below shows the accelerator at work on the Boston subway system. At this moment we see a live, interactive view of routes, expected stop times, and the position of the train en route.
The magic happens in the “Stop Times” chart. That’s a new open-source Spotfire Mod, written by Glenn Hoskins. It shows a real-time view of stops and a live prediction of schedule deviations. The numbers in red (“+1:09”…) are generated by machine learning in real-time. They show expected delays so human operators can anticipate and fix problems before riders notice.
Driverless doesn’t mean human-free. Indeed, human judgment is more important as automation increases and this accelerator shows how.
Soon, the only one to blame for being late will be you.
Download the Real-Time Public Transportation Accelerator from the TIBCO Community here.
Led by Glenn Hoskins with contributions by Philippe Gabert, Paul Wilson Villena, Kevin Higgins, Japinder Singh, Manish Patel
