Here’s to You, MBTA Bus-Tracking Apps

On days when your commute is bound to suck, the MBTA’s technology makes a bus commute infinitely more bearable.

By | Boston Daily |

A screenshot shows the wait times for a #1 Bus from Central Square.

Let’s take a moment to appreciate how the modern world makes your morning commute somewhat less awful.

It might seem like a strange occasion for such musings. It snowed a whole bunch in Boston, and that means the #1 Buses usually don’t come for 30 minutes, and when they do, they come in packs of three, all of them full of slush-covered zombies who can’t or won’t make room for you to board.

But by now, you maybe have an app that uses tracking data to tell you how long you’ll have to wait for the next bus to come. The MBTA partners with NextBus, providing them real-time GPS locations for their buses, which the app then calculates into an arrival time prediction. The innovation is years old, but let’s just all nod our heads and agree that this app is the greatest thing to hit mornings since the snooze button. In appreciation, The Atlantic Cities today highlighted research that shows just how important these apps have become to the commuters who use them. Kari Watkins, an assistant professor at Georgia Tech, studied people who used a similar app in Seattle. Research showed that people who knew exactly where the bus was were less likely to overestimate how long it ended up taking. Plus, as The Atlantic‘s Emily Badger writes:

In their earliest research on the impact of such mobile tools, Watkins and Ferris identified two other implications that have grown increasingly relevant as apps like this have become more ubiquitous: Riders who used OneBusAway not only perceived that their waits were shorter, they actually waited for less time, too, because the app enabled them to plan their travel better. Why head out for the bus right now, if you know it won’t come for another seven minutes?

What’s more: In surveys of these early OneBusAway users, 92 percent of them reported that they were more satisfied with public transit as a result of using the app.

Anyone who uses this app, especially on days like these when the system is operating erratically, doesn’t need to be told this. Particularly apt is the observation that wait times go down when you can look at your phone while you’re getting ready in the morning or sitting at your desk in the evening, timing your departure for the bus stop accordingly. The thrill-seekers among us know how to game it so they don’t have to wait at all, dashing out just in time to walk straight onto a bus with its doors wide open.

The alternative—standing outside in a snow bank wondering if the buses are running on schedule (they aren’t) or if you arrived two minutes after the last one left (you did)—is a pretty unbearable thought in this brave new world of technologically optimized commute times. The bus goes from being a sad, miserable option to one that’s often smoother than the Red Line. As Badger notes, this app gave transit agencies like the MBTA a really simple way to improve customer satisfaction without improving bus frequencies or even schedule accuracy.

That said, it’s still a smartphone app, which means its not exactly the most populist of transit tools. Buses, in particular, aren’t just for the Droid-wielding commute-hackers among us who want an extra five minutes built into our day. Luckily, these apps have browser versions, so at least you can check your wait time from a computer before you head out the door in the morning. In a dream world where the MBTA had unlimited money, perhaps they would install wait clocks like the ones they’ve rolled out on T platforms at major bus stops. (Just, first, do something about that Green Line, hypothetically well-funded MBTA.)

Despite this technological dream’s limitations, it’s psychologically worthwhile on days when you probably had an extremely annoying commute to appreciate how technology has made it slightly better than it would be otherwise. This writer once showed the app to a friend who had been attending grad school in Boston for years without anyone informing her of its existence. A week later, she texted to say that the app had “changed my life.” So here’s to you, bus-tracking app. You make living in blizzard country slightly more bearable.

  • Jude

    The Catch the Bus app has been around for a few years and already does all that

    • AngryRider

      NextBus utilizes bus location data and uses an advanced algorithm – taking into account historical travel times – to make very accurate predictions. For the MBTA, in addition to providing it’s own distribution of prediction data, NextBus makes an XML/API available for third-party developers to use to build other distribution apps. Catch the Bus is one of these third-party apps and actually won a contest for best app funded by NextBus.

      • Jude

        That’s great! It is extremely popular!

  • Matthew

    Nextbus (the company managing the data) also has a text message interface for people without smart phones. They may have a telephone option too but I have not used it.

    For those without phones or computers, SF MUNI uses the same tech and has managed to widely deploy digital signs at bus stops, not just subway stations, so it’s not impossible.

  • David Duff

    The *potential* usefulness these apps is high. however, if availability or accuracy of the tracking data goes much below 100%, the overall usefulness of the apps drops off quickly (to below zero). As someone who uses several of these apps *extensively* on a daily basis, I can report that they don’t live up to their potential for the following reasons:

    1. Sometimes buses simply don’t show up in the tracker. When this happens, I point it out to the drive and ask if they know why; apparently, drivers know absolutely nothing about the tracking system or how it works (nor why it sometimes fails).

    2. I travel daily via Alewife, which is the origin for the bus routes I take home. Live tracking performs poorly for those routes. Tracking is useful and accurate when you can see what buses are moving along the route and estimate their arrival time at your stop or when buses operate on a simple “loop” – for example where an inbound 76 bus immediately becomes an outbound 76 at the terminus. This simple model does not seem to match the reality of Alewife. On one hand, there may be substantial delays between an inbound bus arriving and the outbound bus departing (buses often sit parked opposite the passenger pickup area). On the other hand, there may be buses that come in on one route and go out on another. The net result is that tracker predictions at Alewife rarely match reality.

    3. For over-subscribed routes, I still don’t get a reliable indicator of when/whether you will be able to board a bus. For example, yesterday, I waited at Alewife for an outbound 76 bus, only to have it arrive, fill up and leave (full) without me (probably due to the previous scheduled bus on the 76 or 62 being late or cancelled). This is not the fault of the tracker, I realize.

  • Doconnor

    “which the app then calculates into an arrival time prediction”

    Actually NextBus provides both the position and the arrival time prediction to apps.

    For the problem of overloaded vehicles, my web site TransSee, can show the gaps between vehicles color coded based on if they are above or below average, which indicates how full they might be. However it doesn’t work for the first bus on the list. I was planning on implementing the gap for the first bus, but I never got around to it.