Posts about Bike Sharing
When a bikeshare station is empty, or an app tells you it's only got a bike or two left, should you just try another station? In both cases, waiting it out is often the best bet for getting a bike most quickly.
A team of data scientists at TransitScreen recently put some thought into how to make information about bikeshare more helpful. Rather than just showing "0 bikes" at an empty station, for example, we wondered whether we could predict how long you would wait to get a bike at that station.
Using Capital Bikeshare data from 2012 through 2014, we calculated the probability of the bike count increasing or decreasing within five minutes. We did this for each station, then we smoothed this probability across hours, days, and months.
We looked at five different stations where more than 10 bikes per hour were turning over, but ended up looking most closely at the Thomas Circle station at 14th & M St NW. This 33-dock station was particularly interesting since its place on a border between residential and commercial neighborhoods leads to rapid turnover throughout the day.
We noticed the wait was most predictable at bikeshare stations that see a lot of turnover, like Thomas Circle. When that's the case, it's highly likely a bike will be available within a reasonable amount of time (even if you're in a hurry). And when there aren't many bikes left at a station, there's still a good chance that one will be available within a given five minute stretch.
If it's rush hour, waiting is a good call
Imagine you're working near Thomas Circle and looking to run an errand at 5 pm on a Tuesday. You rush over to the bikeshare station only to find it empty. What should you do?
The data shows that if you wait for five minutes, there is a 50% chance a bike will appear. Considering how long it might take to walk to the next-closest station, five minutes might not be so bad!
If the same situation came up at 1 pm, however, you'd only have a 20% chance of getting a bike within five minutes. Waiting would probably be a waste of time, and you might want to find another bikeshare station (or choose another transportation mode altogether).
Chance of bikes appearing within five minutes at different times of day. The station is Thomas Circle, the time is a weekday during May. Graphs from TransitScreen.
It's rare for a station to go from having few bikes to actually having zero
Let's say that next week, at the same time, you check an app like TransitScreen before leaving your building. This time, the dock isn't empty...but it only has one bike.
What's the chance there won't be any bikes left after the five minutes it takes you to walk there? It turns out even at the busiest time, evening rush, it's still 60% likely a bike will still be there when you arrive.
Chance of a single bike remaining after 5 minutes at different times of day. Station is Thomas Circle, time is a weekday during May.
Similar ideas hold for returning bikes to full stations
It's not uncommon for people to get "dockblocked," which is when you go to return a bikeshare bike but the station is full.
Anecdotally, this seems even more common than people waiting at empty stations. It's possible that's because it's just easier to see a person waiting with a bike rather than one who is empty-handed. It could also be that people who need to return bikes are willing to wait longer because they've just finished a ride and they're feeling tired.
Either way, like with empty stations, we predict that in a lot of cases, it makes sense to wait rather than find another station.
We can do similar studies for other stations
We used Thomas Circle as our example, but as long as it has open bikeshare data, we can study stations with high bike turnover in any city— I'd like to thank Erin Boyle for doing the coding and analysis for our recent research. Dan Gohlke shared his CaBiTracker data store with us, and we used open source code from the Data Science for Social Good group.
I'd like to thank Erin Boyle for doing the coding and analysis for our recent research. Dan Gohlke shared his CaBiTracker data store with us, and we used open source code from the Data Science for Social Good group.
The City of Alexandria might not follow through on plans to add 16 new Capital Bikeshare stations throughout the city this year. But if it does, city staff have identified the general areas the new stations are likely to go.
Capital Bikeshare stations overlaid on crowdsourced demand map (Click to enlarge). Map by the author from City of Alexandria data.
City staff presented the expansion information at the Alexandria's transportation commission's December. (The overlay map above reflects a slightly updated set of locations I received after reaching out to the city this week.)
The locations are based on the city's public crowdsourcing maps, connectivity to transit, proximity to mixed-use activity centers, and whether the location was within .25 mile of an existing station.
Technical considerations like direct sunlight to power the stations, adequate space, flat ground, and utility clearances will be important in choosing the exact site for each station.
The new stations would be primarily to the east, in Old Town, Del Ray, Potomac Yard, and surrounding areas. But three new stations would add to the cluster in Fairlington, and Eisenhower East will recieve a new station as well. Though there's definitely a demand for stations in West End, activity centers, density, and a lack of nearby stations could make it harder for stations in those areas to be successful.
What else do you notice about the locations?
As US bikesharing continues to boom, it's fun to look back each year and see how systems have grown. Now that we're into the grind of 2015, let's look back on 2014 and see what changed.
2014 was a modest year for US bikesharing expansion, compared to the incredible boom of 2013. Overall, the number of bikeshare stations nationwide increased about 20%, from 1,925 in 2013 to 2,345 in 2014.
San Diego Seattle launched the largest new system, with 117 49 stations.
Washington's Capital Bikeshare regained its crown as largest overall network, growing from 305 stations to 347 stations. Last year's champ, New York's Citibike, actually lost two stations and dropped from 330 to 328. Chicago rounds out the top tier, with the same number of stations it had last year: 300 exactly. No other system tops 200 stations.
Fourteen Thirteen new bikesharing systems opened nationwide, and four small existing ones closed, bringing the US total up to 49 active systems.
Here's the complete list of all US systems. New ones are marked in bold. Previous years are available for comparison.
|Rank||City||2013 Stations||2014 Stations|
|9||San Francisco (regional)||67||70|
|26||Ft Lauderdale (regional)||25||21|
|27(t)||Salt Lake City||12||20|
|30||Long Beach, NY||13||14|
|31||Washington State Univ (Pullman, WA)||9||11|
|38||Univ of Buffalo (Buffalo, NY)||4||5|
|39(t)||Univ of Califonia Irvine (Irvine, CA)||4||4|
|41(t)||Stony Brook Univ (Stony Brook, NY)||3||3|
|44(t)||Roseburg VA Hospital (Roseburg, OR)||2||2|
|Fullerton, CA (closed)||10||0|
|Georgia Tech (Atlanta, Ga) (closed)||9||0|
|George Mason Univ (Fairfax, VA) (closed)||7||0|
Systems marked with a ~ are stationless bikeshare networks, in which each bike contains a lock and can be docked anywhere. The number of "stations" listed for three of these four systems (Phoenix, Tampa, and Orlando) is approximate and was calculated by dividing the overall number of bicycles by eight. The fourth system, Hailey, has only six bikes but they're located in two distinct clusters, so it seems most appropriate to report two stations.
Counting the number of bikes rather than stations would be a more accurate way to rank systems, but that information is more difficult and time-consuming to obtain.
Correction: This post originally reported that San Diego's bikeshare network opened in 2014. It was originally scheduled to do so, but delays pushed its opening to 2015.
Cross-posted at BeyondDC.
Throughout 2014, DC and New York have jockeyed back and forth over which city's bikeshare system has the most stations in the United States. But who has the biggest stations?
DC currently leads in the number of stations race, 335 to 324. But the number of stations only tells part of the story. New York's stations are vastly bigger than DC's, and by far the largest in the US.
New York's biggest station, which is outside of Penn Station, has a whopping 67 docks. It's almost 50% larger than the next city's largest station.
Here's the number of docks at the biggest station in America's main big-city bikeshare systems:
|Rank||City||Largest station||Docks at largest station|
|1||New York||Penn Station||67|
|5||Minneapolis||Coffman Union and Lake/Knox||32|
|7t||San Francisco||Market/10th and 2nd/Townsend||27|
Cross-posted at BeyondDC.
Regular riders of Capital Bikeshare have cut down on their use of rail and bus transit, a new study shows. This is particularly strong for those in neighborhoods a short bike ride from downtown DC.
In these maps, each circle represents one zip code in which researchers Elliot Martin and Susan Shaheen surveyed CaBi users. The number shows how many responses they got in that zip code. Red is the percentage of those people who used that mode of transit less (rail for the map above, bus below). Green is for those who used it more, while yellow is those who didn't change.
It's not only transit which riders are using less. CaBi users also have cut down on car trips and probably even replaced some walk trips with bikeshare.
This isn't necessarily bad for transit. The places where this effect are strongest also happen to be the places where transit is most congested. On the busy Metro lines at rush hour, the trains are full into downtown DC; it's just as well if fewer people are hopping onto an already-packed train at, say, Foggy Bottom.
And many of the people who ride Bikeshare still use transit some of the time. They might still ride it in bad weather, but at other times avoid it at its most congested, or at times of poor service, like the very long waits on weekends during track work.
One potential danger, though, is that if there is lower demand for service on weekends (thanks to a bicycle alternative), that could make it less likely local jurisdictions want to pay for more frequent transit service at off times, even though not everyone can substitute a bikeshare trip for a transit trip.
Meanwhile, in Minneapolis (which has much less rail transit), the study found that many people increased their usage of rail, perhaps because the bikeshare system helps them access transit much more easily.
Eric Jaffe writes in Citylab,
Overall, the maps suggest that bike-share, at least in Minneapolis and Washington, is making the entire multimodal transit network more efficient. For short trips in dense settings, bike-share just makes more sense than waiting for the subway—
it's "substitutive of public transit," in the words of Martin and Shaheen. For longer trips from the outskirts, bike-share access might act as a nudge out of a car— it's "complementary to public transit."
Honestly, once I started bicycling (first with Capital Bikeshare, and then more and more with my own bike) I personally cut down significantly on using transit. But I live in a downtown-adjacent area where it's a fast bike ride to many destinations; for others, that's not the case, and transit is best for their trips. I also still ride transit some of the time.
Some people in the survey also increased their use of transit. The more transportation options people have, the more they can choose the one that best matches their needs. The road network is already quite comprehensive (though often crowded). We need to offer everyone high-quality transit and bicycling as alternatives so that they can use each when it's the best choice at that time.
Many of the services that call themselves "sharing," like "ridesharing" (Uber, Lyft), "car sharing" (Zipcar, car2go), bikesharing (Capital Bikeshare), "home sharing" (Airbnb), and others, are not really "sharing" as we typically think of the term. Do we need up with better words to describe these new business models?
The "sharing economy" (early on called "collaborative consumption") is a rapidly-growing sector. Most of its businesses allow people to temporarily use some good for a fee where typically, and formerly, people would own it (like a bike, a car, or an apartment).
But many commentators have pointed out that the term "sharing," at least as we learned it as children, generally means letting people use something you have for free, not renting out something you have, and definitely not a company owning a bunch of things which it rents to people or paying someone to do work on your behalf.
Companies like Uber and Lyft have been dubbing their services "ridesharing." These companies contract with drivers who can make money by offering rides. Jason Pavluchuk from the Association for Commuter Transportation argued that calling these services "rideshare" made it harder to advocate for other models that more aptly deserve the term, like carpool and vanpool services where people actually ride together.
There's also slugging, a longstanding practice where people commuting, such as on I-95 in Virginia, pick up other people at a designated spot who are going to the same destination. (The drivers don't charge for this; they do it to get the right to use the carpool lane.)
Uber and Lyft are really new variants on taxi service. They let people use a car they might already own (though Uber is also offering loans to drivers to get new cars), but they are still doing it as a job. If you use such a service, you're not sharing someone's car; you're paying them to give you a ride.
Other companies like Sidecar have envisioned a model where people already driving from one place to another offer rides to someone who happens to be going the same way. That's a little bit more "sharing" than the app-based taxi-like services.
Services like Zipcar and Capital Bikeshare also could have somewhat more of a claim to the term "sharing." In those cases, at least, there is a pool of vehicles which multiple "members" all use together. They all pay, but basically are pooling money to have a shared resource instead of owning.
What do you think counts as sharing? Is there a better term for these services?
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