Smarter Cycling Series: Predictive Analytics make Velib’ a Public Transport like the Others

20 Dec, 2016
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As part of our work to help cycling and the bike industry into the world of smart, connected and shared mobility we are working with visionaries and leaders who are setting the tone in this new mobility. We are going to be inviting some of them to share their thoughts and visions with ECF.com in the coming months.
Clément Collignon is responsible for all things non-technical at Qucit, a French company that gathers data related to urban mobility and provides consulting services to implement optimal strategies for operating transport infrastructure. Clément varied experiences help him smoothen the daily operations, and lead the business development for the company.

For a long time I have been thinking it should be possible to go from the subway to the bicycle without difficulty. Thanks to the partnership between the Paris Region Transport Authority (STIF), Géovélo and Qucit, this dream comes true!

Even though the RER is sometimes crowded, especially during rush hour, it remains a privileged way to go in and out the centre of Paris. Many people in the Paris region use it every day to get to their work or study places. Thus 1.2 million passengers travel daily on the RER A: the most used suburban train route in Europe!

But after half an hour in the RER, you may want to stretch your legs. Why not take a bike ride rather than take the subway to get closer to your final destination. Thanks to the integration of BikePredict API (Application Programmable Interface), developed by Qucit, the Vélib' becomes today a public transport like the others. Everyone can use the STIF Vianavigo route calculator to choose a route that uses Vélib'. And most importantly, one is sure to find a bike when going out on the street and a station to drop it near its destination.

How does it work? 

The algorithm lying underneath BikePredict is a predictions-providing machine. Every minute, we analyze bikes’ availability, and a whole bunch of variables to understand what is happening in the city. Thus, we can predict the number of bicycles that will be in a station, and perhaps more importantly the chances of finding a Velib when arriving at a given station.

From there, our friends at STIF just select the Velib stations near a metro entrance. Selection is based on the distance to the station and the chances of finding a bike there when the user will get out of the metro. For example, only stations with more than 90% of bikes will be selected. And the user will be directed to a station where he is also sure to be able to drop his bike the moment he arrives. This way, Vélib' becomes as reliable as if you had your own bike at the exit of all the metro stations!

How it actually works

Mr. Robinet works in a tower in La Défense. Hard day. Too much responsibility. He called his wife at 7pm to warn her that he would not be there until 9pm. He leaves his office at 8pm. Under the Grande Arche, it’s passed peak hour but there are still many people. Before closing his workstation, our friend checks vianavigo.fr to determine exactly at what time he will arrive, and decide if he asks her to wait for dinner.

Suggested itinerary: take the RER A to Les Halles, then take switch to the metro. 33 minutes. He’d rather switch to a bike so when he arrives in Les Halles, he checks again on his mobile and is proposed a bike itinerary. Works for him. He'll be able to get some fresh air. SMS to madame when exiting the RER: "I'll be there at 45". No risk of delay, pura vida. Arriving at Les Halles, he goes to the ETIENNE MARCEL Velib’ Station, where he knows he is going to find a bike. All works as expected: he takes out his Navigo pass and rides his bike. 15 minutes later, station REPUBLIQUE FERRY, successful rendez-vous with a dock, as if he had booked his place in advance.

All but one problem remains: the bike that rides by itself. Yet this is only in the movies, and even our most beautiful algorithm can do nothing about it.

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