Public transportation system data – like timestamps of train arrivals, for example – is cool for planners and data analysts, but how does that translate into helping everyday riders?
Ben Shepherd, in his presentation at Transportation Techies’ Metro Hack Night VIII, articulated this disconnect between planners and riders: that a commuter’s journey begins at the decision whether or not to ride the system, well before reaching the station. Yet reaching the station is where trip-planning apps begin.
Considering this entire journey – from deciding which mode to arriving – in a trip-planning app could influence more people to walk to the station instead of drive or call an Uber or Lyft. Metro, take note.
The more information, the better your ride is
MetroHero’s James Pizzurro returned to the stage to explain how the app (which he and the co-founder spent three years developing) is now shifting its focus to individual riders who want to understand what their current commute will look like. Users can now save their favorite trips in My Commute, providing a no-effort glance at the information most relevant to them. This provides an ETA for riders and pulls WMATA alerts, escalator or elevator outages, and tweets relevant to the trip. All of this makes it easier for a commuter to make a quick decision on their options for getting to or from work.
If you want to explore Metro service beyond your particular ride, MetroHero allows users to dig into the details of individual lines’ performance, including average headways over the past hour, schedule adherence, and active eight-car trains, among others. Pizzurro made a point that this application program interface (API) is open to the public to develop even more apps (instead of developers having to rely on Metro’s not-always-accurate GTFS) – which is exactly what another presenter did.
Ben Shepherd used MetroHero’s open data to build a tool that helps commuters better understand how their commute will go by framing a familiar question in a unique way: how does walking affect which train someone can catch?
The key part of this journey planner is that others only consider the time it takes to reach a station, but not the time it takes to get to the platform after entering the station where one can board the train.
Shepherd found that at the L’Enfant Plaza stop, it takes a minimum of 90 seconds to walk from one station entrance to a Green Line platform – enough time to determine if he would make a train or have to wait for the next one. In addition, the app, which is still under construction, shows users how fast they would have to walk to catch trains arriving at the closest station: should they run, take it easy, or is there no chance of making it at all?
James Collins also created a tool to give himself a quick glance at how his specific train commute looks at any time with DC Metro Monitor. Collins’ map shows the Metrorail system with its real geography, with real-time locations of animated trains as they move along their lines. Users can toggle lines and train directions on or off, select stations for train ETAs, and have a quick view of WMATA alerts, all to inform them of their commute.
Holograms pick the best route for you
Josh Tauberer analyzed train data to discover the most effective transfer point for a commute between the Columbia Heights and Rosslyn stations. Efficient transfers are not always what they appear, but usually, they are. WMATA’s open data allowed Tauberer to experiment with the most efficient method of traveling from his home in Columbia Heights to his job in Rosslyn. Metro’s system map leads riders to assume that the quickest path between the stations involves one transfer at L’Enfant Plaza, but can one be so sure?
Using real-time train information, Tauberer had a virtual version of himself ride the system at various points during the day, duplicating himself at each possible transfer station to compare those trip times against if he continued along to the next transfer. Tauberer’s analysis revealed that transferring twice, at Gallery Place and then at Metro Center, is typically about four and a half minutes faster than a single transfer at L’Enfant Plaza Station.
For Transportation Techies and advocates who want to do more with their projects, Ray Cha shared the Nature of Cities’ Transit Data Toolkit, a trove of information to guide open data users through obtaining and using the information effectively.
Join us at the next Transportation Techies meet-up on October 24th! Photos by Jenna Fortunati for Mobility Lab.