Data Sharing: Lyft HotSpots

It’s hard to deny that private companies (Uber, Lyft, Bridj, SideCar, Chariot, Leap, etc.) are providing new mobility options and helping address some gaps in a city’s transportation system.

There are many questions about how they impact public transit. Is it all doom and gloom — like the Google bus protests and backlash against the Leap luxury bus? Or can there be a better kind of peaceful co-existence? Can we make transportation better and easier for all riders?

As I’ve written before, I think the opportunity lies in data. Through their technology, these companies are collecting unprecedented data around travel behaviors. And through successful data partnerships with the public sector, we can design a better, more inclusive transportation experience for everyone.

Data-driven approaches to the delivery of key public services like transit are starting to take hold. In Boston, we’re seeing Uber taking the lead on a data exchange. And in Oregon, the Department of Transportation has partnered with fitness app Strava to use their route data to inform bicycling infrastructure investments. But these partnerships shouldn’t be anecdotal examples- they should be the norm.

A Closer Look at Lyft’s HotSpots

In San Francisco, it’s been reported that one-third of all Lyft rides are carpooling trips through Lyft Line.

In Lyft Line’s next iteration (March 2015), HotSpots were introduced, and riders get picked up at designated intersections in the “Drive Happy District” (anywhere in the City to Stanyan and Cesar Chavez Streets) for a fixed price. In the following weeks, they slowly ramped up the number of pickup locations, announcing 100 new HotSpot areas on April 10. Boom, ridesharing had gone widespread carpooling.

It’s great to see Lyft investing in a service that supports aggregated trips, rather than individual rides (gotta love those Vehicle Miles Traveled reductions). And through Lyft’s service, people’s attitudes are changing around the necessity of personal vehicle ownership.

I love Lyft. I think they’re super progressive: their mission is really about sustainable transportation and building community, and female leadership is key to their company culture. But my spirits fell a little bit when I read their announcement. Their Hot Spot Map was a graphic. Yes, I get the point is that you activate certain HotSpots when you’re standing near one.

I pity the transportation planner who has to use Tinder icons to make key decisions about Muni.

For a company that has been known for “playing nicely”, I would love to see them be more friendly in the data-sharing space. So I’m giving them a head start: this weekend, I played around on the Lyft app to geolocate all of their current HotSpot areas. Shoutout to the awesome Lyzi Diamond for teaching me how to use CartoDB. If you’d like the geodata, it’s all here in this Google Doc.

Some findings

Using the SF Planning Departments Planning Areas shapefile as neighborhood boundaries, I mapped out what neighborhoods have the most HotSpots.

The results aren’t particularly surprising- they’re definitely catering to where tech employees commute to work and hang out (looking at you, SoMa and The Mission). Interestingly, I noticed that Chinatown, is the only neighborhood within the Drive Happy District to be overlooked with a HotSpot area.

I’m just getting started with the analysis, but I think next steps will include investigating the relationship between HotSpots and transit stops. A correlation between HotSpots and BART could point to ridesharing services acting as a last mile solution. However, it’s also possible that these locations could present challenges for the delivery of public transit — like causing delays by blocking Muni loading and unloading zones. I’m excited to continue my research.