DC Bikeshare’s uphill problem (and why I understand that physically now)
After months of procrastinating, I bought a yearly membership to Capital Bikeshare. It’s been a good month now and I’ve been using it primarily for commuting. The ride is not busy at all, as the majority of my route rides along the Pennsylvania Avenue bike lanes, which are in the center of the road and have small breakdown lanes on either side.
But oh those Bikeshare bikes are heavy. At 40 pounds and three gears (at settings of “too loose to peddle” “hill, I guess” and “will move you more than 2 miles an hour on flat surfaces”), as the hero/insane person who used a bikeshare bike to race a triathalon (!) can attest, they are sturdy but painful to push against the smallest hill or stiffest wind.
“Whoever said that trail was flat, should try riding it on a Bikeshare,” hero/insane person Jefferson Smith told DCist.
I have one notable hill – 15th street along the Treasury building – that fortunately has its own offset bike lane. Granted, I’m not in the best bicycling shape but that hill is long and deceptively steep. After a month I’ve already felt faster on straightaways and gotten better at picking up from a dead stop, but when I turn onto 15th, the next three blocks have never ever gotten easier. A phantom pain in my knee has generally stopped protesting when I go up the hill, but it’s still a real work out for my legs. Is it the 40-pound behemoth I’m dragging uphill along with my own weight? Or is it just a nasty hill?
Left and Leaving Co-efficient
That being said I have throughly enjoyed being a bike commuter, even on a heavy bike. I see plenty of people doing the same, although only about a 1/4 or a 1/3 are doing so on bikeshare.
Capital Bikeshare makes no secret that the system is designed for short around-downtown trips. The average trip is just over a mile. But there are stations everywhere around the city. For those who aren’t familiar with DC, downtown is set in a bowl. Which means, if you go far enough north or southeast (south is just Virginia, and that’s another story) you will be climbing some serious hills before it becomes flat again.
As I was signing up for Bikeshare, I noticed that they had a system data tab where they made public some of the data associated with the bikes. Among the data released are arrivals and departures by station. As a about-to-be new member I realized this could be helpful to me – noting which stations had high general turnover and which ones were likely to be empty/full.
But then I got a bit fancy.
The methodology of the following analysis was done by essentially making it up, using a gut-level understanding and basic math skills. I took one statistics class in college, in which one day I walked out, returned a library book, had coffee and lunch, and returned to my seat, all as the professor stared at the board, never noticing my absence. So be forewarned, but I think this makes sense.
Here is the July 2012 Arrival and Departure data for the 11th and Kenyon stop:
- Departures: 1828 Arrivals: 1364
(A quick moment to explain: bikeshare “rentals” are one-way. You take a bike out at station x and drop it off at station y. You may later take another bike from station y and drop it at station x, or even z, but that’s a separate trip. This means that in the month of July, 1828 bikes left the 11th/Kenyon stop and 1364 bikes were dropped off there. Bikeshare has vans that move bikes around to different stops as they fill and empty).
As I scrolled through the data, I noticed that some arrival/departure numbers were fairly equvalent, while others were several hundreds, even thousands apart.
So I made another column: Difference between departures and arrivals. Here’s the top 10.
|Idaho Avenue and Newark Street NW||335|
|Georgia & New Hampshire Ave NW||338|
|Lamont & Mt Pleasant NW||378|
|39th & Calvert St NW / Stoddert||401|
|Columbia Rd & Belmont St NW||430|
|11th & Kenyon St NW||464|
|Park Rd & Holmead Pl NW||474|
|Adams Mill & Columbia Rd NW||504|
|14th & Harvard NW||562|
|16th & Harvard St NW||1008|
Hey there 16th and Harvard.
Now this is the top 10 of difference in departures; these numbers represent how many more bikes are leaving a station than arriving in a month (July 2012). The top 10 difference in arrivals would show how many more bikes arrived in a station than left it (none of these numbers include manual transfers by Bikeshare, I assume, so this is customer behavior.)
But the simple difference tells us nothing in relation to how busy the particular station is.
The stop by 7th and Maine SW will have nowhere near the volume of the stop by 21st/Penn, near many office buildings and a university . So a difference of 50 at Penn isn’t as significant as a difference of 50 at Maine.
Instead, what’s more interesting is the difference between departures and arrivals as a proportion of total trips. Please pause for math:
(Departures – Arrivals)/(Departures + Arrivals) = the Left and Leaving co-efficient.
The Left and Leaving co-efficient is named after a favorite song from the first year I lived in DC, by the underrated Weakerthans, but that’s mostly for my own amusement. What is represents is how significantly (NOT in a pure statistical sense ) each stop “left” more often by users. A stop with a high L&L co-efficient will have a systematic empty problem, possibly not just at rush hour. My guess is that bikeshare is already very very aware of this.
BUT WAIT, YOU’RE FORGETTING – yes I know: what happens to the L&L with stations where there are more arrivals than departures? I’m not going to bother reversing the top part of the equation when it can effectively show me a spectrum. It can have a negative value. Stops with high negative L&L’s in theory will have the opposite problem – always being full.
An example of a negative L&L station: 13th and D NE – Departures – 1539 Arrivals – 1568 L&L: -0.01609323.
So what does the L&L co-efficient tell us, really? Let’s look at the top five highest and lowest L&Ls
|39th & Calvert St NW / Stoddert||Washington, DC||701||300||401||0.4005994006|
|36th & Calvert St NW / Glover Park||Washington, DC||445||239||206||0.3011695906|
|Tenleytown / Wisconsin Ave & Albemarle St NW||Washington, DC||711||383||328||0.2998171846|
|Idaho Avenue and Newark Street NW||Washington, DC||730||395||335||0.2977777778|
|16th & Harvard St NW||Washington, DC||2641||1633||1008||0.235844642|
|C & O Canal & Wisconsin Ave NW||Washington, DC||1866||2435||-569||-0.1322948152|
|7th & Water St SW / SW Waterfront||Washington, DC||667||881||-214||-0.1382428941|
|Lynn & 19th St N||Arlington, VA||1016||1354||-338||-0.1426160338|
|Georgetown Harbor / 30th St NW||Washington, DC||1345||1846||-501||-0.157004074|
|Ft Myer Dr & Wilson Blvd / Rosslyn Metro||Arlington, VA||695||959||-264||-0.1596130593|
I’ve removed stations with less than 100 trips total for issues with sample size, but the first thing I notice is the high L&Ls are all at the top or midway up very steep hills. Bikeshare customers are leaving 16th and Harvard, near the Columbia Heights neighborhood, but they aren’t returning on bike. And with the exception of the 16th/Harvard and the Tenleytown stop, all are in exclusively residential areas. The other two are also very residential but are nearby commercial strips.
The lowest L&L’s? Yes, they’re generally downhill, but most places in Washington’s core are. Three are touristy or entertainment areas, and the other two are relatively close-in Arlington commute stops. With the Arlington stops, this suggests that commuters are more likely to take a bike back home rather than into work. At Georgetown Harbor, everyone is likely heading over for a meal or a drink at the end of the day, maybe getting a bit too tipsy to take a bike back. C&O is likely very busy and has many trips where tourists are taking the bikes out along the towpath and returning them to the same station.
None of the conclusions from the L&L co-efficient are particularly world shattering. I’m not shocked that people don’t like powering a 40 pound red monster up a massive hill on a busy city street.
But it’s nice at the end of the day when data matches up with the aches in your bones.