talk cities

Analyzing Berlin Carsharing

Scraping months of carsharing to reveal hidden patterns in urban mobility.

Analyzing Berlin Carsharing

When people take carsharing to go places, they often leave behind an unbalanced system.

That’s because often, people tend to enter or exit the same areas at similar times, together.

How can we predict this, and optimize carsharing fleets to better serve urban mobility?

This is exactly what I explored in my bachelor thesis and further spoke about at PyData Berlin.

GWR of carsharing trip starts and transit POIs in BerlinGWR of trips vs transit POIs

PyData Talk

Once the conference uploaded the recorings, you’ll be see my talk here.

Until then, you can look at the slides here.

Thesis

or download it here