Here’s your chance to analyze and visualize the movements of the Metrobus fleet.
In anticipation of the upcoming Metro Hack Night, Metrobus planning staff has generated an automated vehicle location (AVL) systems data set. The data set, for five days in October, shows the time that each Metrobus was at each stop over the course of the day, the buses’ dwell time, and a comparison of actual stop time to scheduled stop time.
Real-time arrival sings at Metrobus stops around the region are powered by automatic vehicle location (AVL) systems on-board buses.
What can be done with this kind of data? Here are a few ideas:
- Look at how the running times for routes varies across the day
- Calculate vehicle speeds across the region
- Dive deep into on-time performance
- See how dwell times affect running times, speeds, and on-time performance
- Map the movements of Metrobus vehicles over time
- Get a better understanding of Metrobus operations, including how vehicles are interlined among routes and the number of different variations of some routes
Come on techies! Dive in and find new and inspirational ways to look at this data.
Please post links to your work in the comments!
Metrobus_AVL_Oct_2016.zip (319 MB zip file)
And some brief documentation:
Metrobus AVL Data Dictionary(.docx, 13 KB)
Metro is committed to working with the developer community – we’ve launched a real-time train position API, are hosting developer coffee chats this Wednesday (7/27) from 4pm to 6pm, created a developer google group, and are seeking submissions for an App Gallery!
If you frequently monitor Metro news, you’ll have already seen some of Metro’s latest developments regarding the commitment to open data and third-party developers. Most notably, Metro last week released a real-time train position API, making it possible to identify the specific locations of trains in the system at a given time.
Screen capture of Metro’s internal real-time train positions map. Now, third-party developers can make their own versions of this using a recently released data feed.
We can’t wait to see what you do with the data. But we know you’ll have questions. That’s why we’re hosting an informal “Coffee Chat” this Wednesday, July 27, at Compass Coffee on F Street (near the Gallery Place-Chinatown station and 70/74/D6 buses). Stop by any time from 4pm to 6pm to say hello, show us something on your computer, or ask us questions!
Two other notable updates, Metro now has created a google group to serve as the intra-developer community forum and will be launching an “App Gallery” to showcase apps available for the Metro system.
To help the region and our partners plan alternatives and mitigate the impacts of SafeTrack, Metro releases rail ridership data applicable to this important maintenance effort.
Rail Link Volumes: This data describes the number of customers on board trains between two contiguous stations, for a given hour of the day, then assigned to rail links. For example, the link volume from Bethesda to Friendship Heights is the sum of everyone who boarded upstream, minus those who exited at or before Bethesda. This can be useful for planning SafeTrack mitigation efforts because it gives a first-order estimate of the potential demand for a bus bridge, for example.
Online Interactive Map of Metrorail Link Volumes, average weekday and Saturday in May 2015
Metrorail Link volumes, average weekday in May 2015, by hour, by line color (580kb, .xlsx)
See how seasons, land use, and service drive trends in rail ridership at the station level, in this new data download.
This latest data download shows Metrorail ridership by station, by month, for the last five years or so. It hints at the complex factors driving rail ridership – from short-term effects like weather or service changes, to long-term trends like real estate development and office relocations.
We see a few tidbits in this data:
- Seasonal trends: rail ridership follows a predictable pattern each year – peaking in the summer and around Cherry Blossoms, and reaching lows around the holidays. Compare the high seasonality of Arlington Cemetery to a more commuter-oriented station, for example. Ridership in the summer at that station can quintuple over its winter base.
- Weather impacts: see how the blizzard this past January lowered the average for the month as service was shut down.
- Service changes: See how the opening of the Silver Line shifted riders from Orange to Silver in July-August 2014.
- Land Use is key! Look at the recent growth rates at stations like Navy Yard and NoMa (formerly New York Ave.), reflecting the new jobs and residences near those stations.
Metrorail Ridership, by Station by Month, 2010-2015, Average Weekday (.xlsx, 120kb)
Metrorail Ridership, by Station by Month by Period, 2010-2015, Average Weekday (.xlsx, 630kb) (Added 3/30/2016)
Notes: these numbers are raw entries for an average weekday in the month, including snow days, excluding holidays when we did not run a weekday schedule. The numbers are for trend analysis and will differ slightly from those we report in financial statements, which undergo additional data scrubbing and normalization.
What do trends you see?
New data download features rail ridership by origin, destination, day of week, and quarter-hour intervals.
Subset of the visualization made by BioNrd aka Mike from our October 2014 data download data.
As you’ve probably noticed, it’s been a while since we’ve released a fresh batch of Metrorail ridership data. Continuing the spirit of openness, we have recently uploaded data from October 2015 in CSV format. (The number of rows is too great for Microsoft Excel).
This new dataset includes day of week data, so you can begin to investigate impacts of evolving workplace policies such as compressed work schedules. You can also compare it to October 2014.
In the past, we have seen a lot of innovative analyses of the data we share. Perhaps the best so far was a visualization of Metrorail station entries and exits by station by “BioNrd” aka “Mike.” What else can we learn from this dataset?
We analyzed Metrorail, Metrobus, and MetroAccess ridership for all Maryland residents in response to the Maryland Legislature’s data and analysis request. Newsflash – we have customers from across the state!
Origins of Maryland Rail Riders
In the 2015 legislative session, the Maryland General Assembly passed the WMATA Utilization Study (HB300),which required the Maryland Department of Transportation (MDOT) and WMATA to analyze the utilization of Metrorail, Metrobus, and MetroAccess every five years. This year’s analysis is based on the most recent Metrorail passenger survey (2012), Metrobus passenger survey (2014), and actual ridership for MetroAccess for an average day in April 2015. Below are some findings that I found most interesting. But more importantly, here is the complete 2015 Maryland HB300 WMATA Utilization Study (native pdf), which includes all the links to the underlying survey data, interactive charts, and analysis.
- 82 percent of Metrorail trips by Montgomery County residents are destined for Washington DC in the morning on a typical weekday;
- 71 percent of Metrobus trips in the AM peak period made by Prince George’s County residents are for work purposes on a typical weekday;
- 3.3 percent of all trips across all Metro services on a typical weekday are taken by Maryland residents from Frederick, Charles, Calvert, Howard, Anne Arundel, and Baltimore Counties and Baltimore City;
- 35 percent of other Maryland residents on Metrorail access via commuter rail (MARC) and Amtrak; and
- 17,600 residents of the District and Virginia reverse-commute into Maryland on Metrorail and bus each morning on a typical weekday (about 5 percent of total system ridership)
Any other nuggets that you found from analyzing the data? Ideas for other ways to graphically represent the findings?
The latest survey of Metrobus riders is a gold mine of information about who our bus riders are, why they travel, and more. Here are the answers to just three questions:
Who’s on the Bus on 16th St. NW? Metro planners and DC residents alike have advocated for a possible bus lane on 16th St. NW, where Metrobuses carry over 50% of the people, are scheduled for about every two minutes, and are frequently bunched and overcrowded. The survey can tell us what kinds of riders use that corridor – giving us clues to what kind of new riders a bus lane might attract.
- Three quarters of S-Line (S1, S2, S4, and S9 combined) riders live in D.C., while the rest hail primarily from Montgomery County
- S-Line riders are younger and more affluent, than the system-wide average for bus riders.
- They are slightly more likely to be car-free and employed by the federal government, but the difference is very small.
Categories: Metrobus Studies 16th Street, bus lanes, data download, demographics, K9, Metrobus Survey, S1, S2, S9, survey, surveys
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…
This new data download from October 2014 includes ridership from the five new Silver Line stations.
Over the past few years we’ve been making ridership data available for download and analysis by the online community. We have received some requests for full origin-destination (O/D) data sets that include the new Silver Line ridership.
These data sets include ridership from October of 2014, and are available by period (AM Peak, midday, etc.) or by quarter-hour interval, for all stations including the five new Silver Line stations. Both sets include daily averages for weekdays, Saturdays, Sundays and Columbus Day.
Note, the quarter-hour data file is to big to open in Microsoft Excel.
Have fun playing around with this data and let us know in the comments what you find. Make sure you check out the other assessments of Silver Line ridership we’ve done.
Jan 29, 2015, 10:00 AM Update: Files have been updated to include total and average travel times for each station pair.
Feb 02, 2015, 11:00 AM Update: Files have been updated to separate Columbus Day from Saturdays using a new column “Holiday”.
May 2013 and 2014 Metrorail ridership data is available: what patterns do you see?
Following up on our last data download of rail ridership from May 2012, 2013 and 2014 are now available. These data now represent three “snapshots” in time of rail ridership, at a very fine level of detail. This data can help answer questions, such as: where is ridership growth the strongest? Which destinations are becoming more or less popular? How has off-peak vs. peak ridership changed?
May 2013 Metrorail Ridership by Origin, Destination, TimePeriod, DayOfWeek (.xlsx, 3.3 MB)
May 2014 Metrorail Ridership by Origin, Destination, TimePeriod, DayOfWeek (.xlsx, 3.4 MB)
We invite you to tell us what you see, in the comments.
Technical notes on the data are the same as the last post. This time, Saturdays and Sundays are shown in the same worksheet as weekdays.