Hi, I’m Robin. Welcome to my website 🎉
I’m a Professor of Transport Data Science at the University of Leeds Institute for Transport Studies(ITS), where I undertake research, develop software and web applications, and teach data science for evidence-based transport planning.
Here you can check out my publications and previous/upcoming talks, with links aplenty to visual/audio/video content that you can read/listen/watch to in your own time 📖🎧📺 I share lots of code for data science and reproducible research, this could be a good place to find resources to get started and try out things if you’re interested in reproducing or building on some of the work that I’ve done (which in turn builds on the work of others as all research does). I also occasionally share blog posts and other things here. If you’d like to get in touch, see here 🚀
I lead the Transport Data Science module, which is available to ITS Masters students and MSc students at the University of Leeds taking Data Science and Data Analytics and Data Science and Urban Analytics courses.
You can find me on various platforms, including Mastodon, Google Scholar, and GitHub.
PhD in Transport and Energy, 2013
University of Sheffield
MSc in Environmental Science and Management, 2009
University of York
BSc in Environmental Geography, 2008
University of Bristol
This paper describes an approach for developing strategic cycle network planning tools. Based on our experience developing and deploying the Cycle Route Uptake and Scenario Estimation (CRUSE) Tool for Ireland, we outline the underlying methods, including disaggregation of origin–destination data with the open source ‘odjitter’ software, incorporation of additional trip purposes, routing, scenario generation, and development of an intuitive user interface that is tested and used by practitioners. Commissioned by the national infrastructure agency Transport Infrastructure Ireland, CRUSE provides estimates of current and potential future cycling levels under ‘snapshot’ scenarios to inform investment decisions. The publicly available results at https://cruse.bike/enable planners, engineers, and other stakeholders to make more evidence-based decisions. CRUSE goes beyond previous work by: modeling networks at high spatial resolution; simulating multiple trip purposes (social, shopping, personal utility, recreational, and cycle touring), supplementing official origin–destination datasets on travel for work and education; and providing estimates of ‘quietness’ (a proxy for cyclist comfort and route preference) at the route segment level. Three network types—‘Fastest’, ‘Balanced’, and ‘Quietest’—help plan both arterial and residential cycle networks. Workshops with stakeholders were used to inform the development of the tool. Feedback shows that the tool has a wide range of uses and is already being used in practice to inform urban, inter-urban, and rural cycle network designs. The approach is flexible and open source, allowing the underlying ideas and code to be adapted, supporting more evidence-based and effective cycling policies and interventions internationally.
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Responsibilities include:
Responsibilities include:
Feel free to get in touch in using the form below. It may be worth considering contacting me in other ways, however, including: