Towards data-driven policy development: the case of London’s built cycling infrastructure

Project Details

Lead Supervisor: Roger Beecham (University of Leeds)
Other Supervisors: Robert Aykroyd, Robin Lovelace, Stuart Barber
Contact Email: R.J.Beecham@leeds.ac.uk
Partners: University of Leeds
External Partners: CycleStreets.net

Start Date: October 2018

In 2013, £913m of funds was allocated over 10 years for investment in London’s cycling infrastructure. Much of this — including guided quietways, protected cycle superhighways and London’s crossrail for the bike — opened in summer 2016. The chief objective: to make cycling ‘a normal part of everyday life  […] something people hardly think about […and] something everyone feels comfortable doing’ (Greater London Authority 2013).

Traditionally, attempts to evaluate such interventions might rely on survey data describing changes in *claimed* behaviour or high-level data from Automatic Traffic Counters describing infrastructure occupancy. The former are often expensive to collect and suffer from numerous (well-documented) biases and the latter are too high-level to capture more subtle changes in behaviour.

This project will instead use new, large-scale observational datasets – from London’s bikeshare, underground and bus network, from route planning services (CycleStreets.net), user-contributed and social media data —  to describe changes in city-wide cycling behaviours pre- and post- the intervention. Crucially, it will identify rich detail around the impact of current investment on behaviour and contribute quantified estimates, under uncertainty, around the impact of future investment.

Applications are welcomed from those wishing to develop expertise in statistical model building, geospatial data and information visualization.

Reference number LE25

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