PlanItMetro

Salaries of actual riders are needed to paint a true picture of Metrorail ridership by line.

The Washington Post recently featured a series of images from the You Are Here project of the Social Computing Group at MIT showing Metrorail median income by line and station.  We were digging into it and realized it uses median household income within a half-mile radius, and not that of the actual riders’ households.  While we’ve mapped low-income riders before, we set out to answer the question, “What is the actual average income of Metrorail riders by line and station?”   Along the way, we developed this interactive data visualization.

Screenshot of Metrorail rider income by station visualization. Click image for full interactive version.

The biggest overall difference between our work and that of the MIT group is higher  household incomes at end-of-line stations on the eastern side of the region.  These stations, while located in lower income areas, have large parking facilities that draw commuters from all over the region and beyond. Read more…

The actual economic benefits of Metro far exceed what planners estimated in 1969, and it’s worth remembering as we consider future transit investments.

In the late 1960s, when Metrorail was nearly about to begin construction, Metro published a forecast of the economic benefits of Metrorail.  The report made rosy projections of the all the travel time and costs the network, then a 97-mile proposed rail system, would bring.  (It also included photos of the pretty awesome 3-D model of a station, including maybe a one-car train?).  Now, four decades later, were the projections right?  Has Metrorail produced the benefits we thought?  The answer is yes, and then some.

Cover of a 1969 report estimating the economic benefits of Metrorail

At the time this report came out, the region was about to make a substantial investment in public transit , probably not unlike today, where we face real choices about whether to invest in Metro 2025 initiatives such as 8-car trains, the Purple Line, or bus lanes.  To quote the report,

Metro is ready for construction. The routes have been selected. The program for local financing has been approved.

How feasible is Metro? Who will benefit?  Will the benefits justify the costs? Is Metro a good public investment for the National Capital Region and its financial partner, the federal government?

The report tallied up all the time savings to riders – former motorists, former bus riders, and truckers – as well as the travel cost savings like avoided parking, vehicle savings, operating cost savings, and more.  It concluded that Metro would save $186 million per year in 1990$, roughly equivalent to $310 million/year in today’s dollars after adjusting for inflation.  Read more…

Latest version of Line Load tool will feature modeled car-crowding numbers.

Many factors influence which car number of a Metrorail train a customer rides.  Infrequent riders may wait for the train near the escalator and board the nearest rail car. Savvier customers may prefer to ensure they are the first to exit at their destination station or have an shorter walk at a transfer station.  Others may board cars based on understanding where seats are more likely to be available.  All of this activity can result in uneven loading of Metrorail cars across a given train, with some rail cars crowded and others near empty.

As we mentioned in 2013, the Office of Planning has an in-house tool that allows planners to estimate how crowded trains are based on origin-destination ridership data. Currently we are in the midst of a few updates, which will include the Silver Line that opened last year.  Another of the new features that we are excited about is a rail car crowding analysis for the system’s most critical segments.  Based on over six months of rail car-crowding data that was collected at selected stations by rail passenger “checkers,” the train-based ridership data will be distributed across the cars so we can estimate what kind of crowding we have by car number, at the peak load points. The following graph illustrates the observed car crowding variations at Gallery Place.

Customers may experience crowded conditions even when the average rail passenger per car (PPC) numbers (PDF) would indicate otherwise. This new feature is an important addition that will help Metro planners better understand the customer experience.  The car crowding analysis will begin to identify which cars of a train tend to be crowded in the peak hours, and which are less crowded.  This information will the be used as a starting point for devising strategies for better spreading customers across all cars of a train.

How do you choose which rail car you ride in?  Other than berthing trains at the center of the platform (see this informative article over at Greater Greater Washington on that topic), what strategies might Metro consider to better balance customers across rail cars?

Ever wonder where rail riders are going to and from? Here’s a map that shows you.

“What are the destinations of riders at Station X?”  It’s a question we get often here. Well, using October 2014 rail ridership data by origin and destination, it’s pretty easy to answer that question – click below for an interactive map.

Click for a larger, interactive version of Metrorail ridership information by origin and destination station

Metrorail has had a huge impact on the region, but as we’ve seen with the Silver Line, it can take decades to get from concept to execution.

One of the questions I hear most often as a planner for Metro is When will a Metro station open in xyz neighborhood, “in Georgetown”, or “at BWI”? It was the first question at the March Citizens Association of Georgetown meeting. My response — “Decades” — often elicits audible groans.

Given last summer’s opening of the Silver Line, we have a case study that can provide insight on how long it takes to plan, fund, and construct large infrastructure projects. The Dulles Corridor Metrorail Project has done a phenomenal job of maintaining a project timeline. Since the region has many recent newcomers, it is helpful to revisit many of the key milestones, as shown below. It is also helpful to remind readers that the Metropolitan Washington Airports Authority (MWAA) was the ultimate developer of the Silver Line (both Phases I and II) and that the project “only” required cooperation among the Commonwealth of Virginia, MWAA, Metro, the federal government, and Fairfax and Loudoun Counties. While just one example, the Silver Line’s long story is not vastly different from other mega-projects happening in the region and across the country.

Timeline for Planning, Environmental Process, Legal and Financing, and Constructing the Silver Line

Read more…

Where and when does Metrorail generate the most farebox revenue? So far the data reinforces the notion that ours is a truly regional system with strong revenue contributions from all jurisdictions – but of course, the story is far more complicated than that…

What kind of rail system is Metrorail? Urban subway? Commuter rail? Hybrid? The answer of course is all of the above. And if that is the case, what kind of ridership and revenue patterns should its stations and system exhibit? High levels of peak revenues with heavy commuter lot usage but relative inactivity during the day? Lower levels of peak period activity but a steady stream of usage throughout the day? Depending on your perspective (and travel patterns) one might argue for either, and it might seem easy to apply a blanket classification to Metrorail and declare that “only urban stations cover their cost” or “commuter stations contribute largely to Metrorail’s revenue picture.”

Well, when you throw the data up on a map, it becomes clear that there are no easy answers, and no one right way to view the revenue picture of our tri-jurisdictional hybrid rail network. Some conclusions from the data are intuitive, some less so. Among them:

• Differences in ridership across stations are bigger than differences in revenue, so ridership is a stronger explanation of differences in revenue than fares. For example, Shady Grove’s average fare in the AM Peak is $5, which is twice as much as the smallest average fare. On the other hand, ridership at Shady Grove is ten times higher than other stations, so the ridership better explains the station’s revenue.
• In the AM Peak, the terminal stations dominate in terms of revenue contribution. Union Station functions as an internal “terminal station,” meaning that the commuter rail and Amtrak connections to Metro are extremely important to the overall ridership and revenue picture.
• Other stations with strong bus or commuter park-and-ride infrastructures also pop in the AM Peak, such as Silver Spring and Grosvenor.
• Note how well the non-Silver line stations in Virginia perform in the AM Peak, as well as the somewhat expected better performance of the Shady Grove branch of the Red Line in the AM Peak.
• In the PM Peak, the core is king. Stations like Farragut West and North, Metro Center, L’Enfant Plaza are producing $50,000 apiece every evening thanks to their job densities, reinforcing the importance of improving their capacity for the future in Metro 2025, as well as their huge importance to revenue today. By comparison, in the AM Peak, only Shady Grove and Vienna approach these levels of revenue at roughly $40,000 per station.
• The New Carrollton and Largo Town Center branches of the Blue/Orange/Silver Lines contribute significantly less revenue than other branches, and this directly relates to the relative lack of transit-oriented development along these spines.  The station areas on these lines enjoy a superb level of rail connectivity to the region’s primary job cores, but without sound transit-oriented investments to-date, they have not yielded the type of ridership and revenue commensurate with the capital investment. Imagine what Metro’s revenues (and farebox recovery) could look like if these segments were properly developed!

We’ve been examining the data ourselves as we continue forward with Momentum’s call for us to ensure financial stability for the Authority and have created the visualization for you to play with. We’d love to know what you see!

Deep explorations into the composition of Metrorail’s customer base shows that Metro has a wide reach – and that the five-day-a-week rider may not be as common as you think.

Metro (bus and rail) moves 1.1 million people per day, right? Well, technically we see that many trips (transactions) per day, but how many individual customers is that?  When you look at your fellow passengers on-board a train, how many are frequent commuters? How many rarely ride? In addition to counting trips, we’ve begun to monitor customers – the number of unique SmarTrip cards and paper tickets used on the system in a month.

We’re starting with Metrorail at first.

Metrorail typically handles roughly 730,000 trips on a weekday, which are generated by about 400,000 unique customers. Some of those customers ride frequently, and others will ride only once in the month.  As the chart below shows, of the 730,000 trips, only about two-thirds are generated by frequent customers.  Not surprisingly, frequent customers dominate more during the peak times.

Typical weekday rail ridership (trips) by customer’s monthly frequency (trips/month)

Surprisingly, over 17% of all trips are generated by customers who take eight trips/month or fewer– that’s fewer than once per week.  That may not seem like much, but in order for infrequent customers to generate so much of our ridership each and every day, there must be a LOT of them! Read more…

In Part Two of this series, we forecast the impact of the region’s near-term development pipeline on Metrorail ridership, using the Land Use-Ridership model. The good news? Metrorail ridership is set to show big gains. The bad news? Your ride just got less roomy.

Just as we were putting the finishing touches on this post, we saw a flurry of news articles detailing the regional market forces that portend increased rail ridership. Millennials choosing not to drive, even as they grow up.  Office parks in far-flung places experiencing devaluations while Metrorail-adjacent areas capturing the lion’s share of new leases.  Marriott announcing that it will seek a transit-accessible location when it moves.  And even defense contractors coming to bat to argue for the economic benefits of the Purple Line. All of this free publicity set us up nicely for what we wanted to share with you – the first results of the Office of Planning’s Land Use-Ridership model as applied to near-term development projects.

The Near-Term Pipeline. Researchers at Jones Lang LaSalle have been compiling a list of actual development projects – under construction, or planned – near Metrorail stations, so that we can forecast the near-term capital needs for the system. A huge amount of development (over 105 million square feet!) is on the books for within a half-mile of a Metrorail station.

Map of near-term development projects near Metrorail, by building type (click for full image)

So, How Much Ridership? What impact will all of this have on Metrorail? We ran these projects through the Land Use-Ridership model, and what we found was both intuitive – and startling. Read more…

We’ve claimed that Transit-Oriented Development (TOD) projects in this region will be critical to Metrorail ridership and sustainability. The good news is that our assertions are grounded in statistically rigorous evaluations of TOD’s impact on Metrorail ridership – here’s how. (Part one of a two-part series).

While factors like fares, service, and the economy can certainly explain some changes in Metrorail ridership, one absolutely fundamental explanation of differences in walk ridership between stations is development.  Why does a station like Landover see only 50 riders arrive on foot each morning, and a station like Crystal City see over 3,000?  Why does a station like Bethesda see balanced ridership in all directions, where a station like Suitland is almost entirely one-direction? Development. Even a simple scatter plot shows that households alone near the station explain 70% of AM Peak walk ridership!

Planning studies have long-posited that transit-oriented development is such a key part of driving ridership, and if that is the case, then TOD is vitally important to Metro’s long-term financial sustainability.  We at Metro needed to quantify this link in a more sophisticated and system-specific way, and so we created a way to calculate the impact of land use changes (household growth, employment growth, new development) on ridership and revenue.

What is a Land Use-Ridership Model? To help, Metro’s Planning Office has built a Land Use-Ridership Model that will predict changes in Metrorail ridership as a result of occupancy changes (growth, decline, new development, etc.) in the station area.  This model helps us get very specific when it comes to modeling the impact of land use changes on ridership and revenue.  It helps us answer questions such as: “When developers build a new apartment building next to a Metrorail station how much ridership and revenue will Metro realize?”, and; “If an office building is proposed at one of four Metrorail stations, which location maximizes ridership and revenue without exacerbating core capacity constraints?”

This tool is based on a rigorous understanding of the link between land use and the rail ridership we see today and is built on “direct ridership modeling techniques” found in academia.  It also focuses specifically on “walk ridership” (which constitutes 38% and 78% of our AM and PM peak ridership), since rides related to bus transfers, parking, and other access modes are less related to adjacent land uses.

To build this, we analyzed the actual quantity of walkable land uses from each station area, assembled detailed information about land uses and densities in those areas (households, jobs by industry type), and also controlled for other, non-land-use factors that shape ridership – like network accessibility. In all we worked through over 200 independent variables in our modeling and also brought in experts from the University of Maryland’s Center for Smart Growth, professors Hiroyuki Iseki, Ph.D. and Chao Liu, Ph.D., to bring their analytical and statistical firepower to the fray.

How We Built It. We defined the walkable area as a half-mile walk along a road network, so we account for barriers like highways and fences.  The half-mile cutoff is a bit longer than the median actual walk distance reported by our riders in the 2012 Metrorail Passenger Survey. For each station and its walk shed, we tested the following kinds of factors: Read more…

Metro’s planners provide tips on avoiding crowds this Cherry Blossom season.

After this long and trying Washington winter, locals and visitors alike are marking their calendars for the 2015 Cherry Blossom Festival. While everyone knows that Metro is the best way to reach the blossoms, PlanItMetro has been digging into the data to help you minimize the crowd crush and maximize your enjoyment of this treasured DC celebration.

What happens to Metro ridership? As we showed last year, the Cherry Blossoms always bring a major bump to Metrorail ridership, especially on weekends and at Smithsonian station. Metro is ready for the increased demand: track work is cancelled, service levels are increased, and our customer ambassadors are out in the field to help with the needs of visitors. So how do savvy Washingtonians avoid the thickest crowds?

Tip #1: Avoid Smithsonian station

On weekends during Cherry Blossoms, the number of customers exiting Metro at Smithsonian dwarfs every other station during daylight hours

Read more…