Green Means Go: Improving Green Line Operations

In late 2017, a small group of designers and developers from Customer Technology embarked on a mission to see if the same software we use to share real-time transit data with customers could also improve operations on one of the MBTA’s most complicated services: The Green Line.

We call this team Glides — or, if you like long names — Green Line Intelligent Decision Execution System.

Over the last year, the Glides team has immersed themselves in information about the Green Line: How trains operate, who operates them, and how those operators make decisions about departures, wait times, and more. They also interviewed Green Line staff, who spoke candidly about the things that can make those decisions slow and tricky — which may make service slow, too.

After a month of exploratory research and synthesis, they moved on to the next phase of the experiment: building software that cuts through the noise of Green Line communications. Their hypothesis was that if track officials were equipped with the right information about performance and schedules, it would be easier for them to communicate with each other, in turn making it easier to deliver more efficient, reliable service to customers.

Supported by Thoughtbot, a local development firm, the Glides team spent the summer building and testing (with real users!) a prototype of this software, a web app for Green Line officials. And this fall, they put that app out into the real world — or rather, into the hands of 22 officials on the B and D branches — for a full-scale experiment.

Why focus on the Green Line?

The Green Line, a trolley route that operates both underground and at street level through Boston and into the suburbs west of the city, has about 200,000 riders every day. It’s one of the busiest and oldest light rail routes in America, operating through the country’s first subway tunnel in the center of the city.

At any given moment, there may be as many as 70 trains in service, with 2 cars per train, and an operator in each car. Dispatchers, supervisors, and inspectors use a dedicated radio channel to communicate with operators, and paper forms to keep track of every departure, arrival, and operator assignment.

Meanwhile, the operators themselves may be navigating vehicle and pedestrian traffic along street-level stops, responding to customer questions and complaints, dealing with disabled trains and weather-related service disruptions, and communicating all of that info to each other and their supervisors on the dedicated Green Line radio channel.

It’s a recipe for complexity, to say the least. And, as our team was building better, faster ways to share real-time data with customers on our website, we knew we could leverage that same software to improve train operations, too.

Why now?

Around the same time that we working on the new MBTA.com, a group of researchers at MIT were partnering with the MBTA for a 2-week pilot of an early version of this exact type of software.

The results were promising: By equipping officials at Riverside with tablets they could use to track train location and departure times, the variability in headway (or, the inconsistency in time between each train’s arrival) decreased by up to 40%, while the average customer wait time decreased by as much as 30 seconds. It was basically like putting 2 additional trains into service at any given time.

We knew it was something we could build on, and the 2 big ideas converged in late 2017 when the initial Glides research period kicked off. The team began prototyping an early version of the app in January 2018. By February, they were building and testing the app that’s now out in the field on the B and D branches.

How does the app work?

Glides, a web app that can be accessed on phones distributed to officials at Reservoir, Riverside, Harvard Ave, and Boston College stations, allows officials to see where trains are, where they’re going, and who is operating them, in real time. They can also enter train departure and arrival information, so other officials can make faster decisions about service needs.

It frees up the Green Line radio channel, which is the only way operators can communicate with each other while out in the field. And, it has the potential to reduce paperwork: officials can track essential operations procedures with just a phone.

What happens next?

The efficacy and usefulness of the app will be tested over the next few months, based on Green Line performance data and direct feedback from staff.

What we think we’ll find is that the people managing the Green Line will be able to make faster decisions about train operations. Which will be a win-win for customers and staff: If it’s easier for employees to do their jobs, riders will get more even, reliable service on the Green Line.

But, if that’s not what this experiment shows us, that’s okay, too. By running this pilot in-house, with our own design and development teams, we skipped an expensive and time-consuming procurement process for software that we might not use.

We’re excited to share the results from our test in the coming months and tell you how we’ll be using what we learned from Glides in future projects. Stay tuned!

Want to join the team that’s helping the T leverage technology? We’re looking for product managers and developers to help roll out improvements to our real-time data, API, digital signage, payment systems, and so much more. Come join us.