How can data help build better cycle lanes?

How can data-driven tools improve transport policymaking? How should researchers use AI responsibly? And why can simpler models sometimes lead to better decisions?

In this episode, we talk about the power of mobility data with Robin Lovelace, Professor of Transport Data Science at the University of Leeds Institute for Transport Studies. His work combines research, software development, and teaching to advance evidence-based transport planning.

We discuss what makes data-driven tools not only open but truly usable, how travel-to-school data can help address biases in cycling infrastructure planning, and how researchers can make their work more accessible and actionable for practitioners.

More about our guest: https://www.robinlovelace.net

Explore the Propensity to Cycle Tool: https://www.pct.bike

Music recommendation of the episode:“Only So Much Oil in the Ground” by Tower of Powerhttps://open.spotify.com/track/4L6cv7W4EpaB62kPoyCQK7?si=YBJ6JtquTVao-coETRy7Vw