05 Aug 08

eBourbaki founder Eliana Hechter [left] and Emily Thornberry MP with competition winners Peter Eccles, Tom Hudson and Ryan Lothian.

A team, including students from Oxford University, has won a competition to come up with a mathematical explanation for why rental bicycle schemes work in some cities and not others.

London Mayor Boris Johnson has announced many cycling initiatives since taking office, one of which is to set up a bike hire scheme similar to that used by Parisians which could see as many as 7,000 hire bikes for use across London.

The ‘Bicycles in London’ competition run by eBourbaki, a social entrepreneurship organisation founded by an Oxford University DPhil student, asked students to model a low-cost network of rental bicycles across the capital.

The winning team created two mathematical models with one describing commuter flow and the other examining the possible configuration of any bicycle stations.

Their models suggested that, for a London-based scheme to be successful, 12 large bicycle stations should be placed near railway stations in central London with 250 smaller stations distributed throughout the West End and the City of London. An average of 20 bikes per small station was found to be the most efficient number.

‘Mathematical modelling is a way of testing any proposed system to be confident that, once in place, it would work effectively,’ said Eliana Hechter, founder and director of eBourbaki, who is currently studying for a DPhil in Statistics at Oxford. ‘We hope the city will work with the winners and consider using their programs in the network design.’

The ‘Bicycles in London’ competition was sponsored by Winton Capital. The winning team of Peter Eccles, Tom Hudson, Ryan Lothian and Caroline Roney from Oxford University and Tom Eccles from Cambridge University were presented with their £1000 prize by eBourbaki, Emily Thornberry MP (head of the All Parliamentary Group on Cycling) and representatives from Winton Capital.

eBourbaki’s next competition is even more ambitious: to challenge students to come up with models to predict the outcome of the US Presidential election based on polling data donated by the Wall Street Journal and NBC. Eliana Hechter said: ‘Our goal is to bring together the private and public sectors, who have abundant modelling problems, and maths students, who have incredible innovative potential.’