Cycling Research Board Annual Meeting

Sustainable urban mobility is an essential foundation for livable cities. Especially in urban areas, public transportation and active modes, such as cycling, are two key components of achieving sustainable mobility. However, planning infrastructure networks for different modes of transport must accommodate distinct requirements and user behavior, often resulting in various, even contradictory, constraints.

Here, we present initial results from an ongoing project on data-driven planning of efficient cycling infrastructure networks, including bike paths and sharing stations, from the perspective of multi-modal mobility, combining cycling with public transport. We focus on the city of Dresden, Germany, where the local public transport provider DVB also offers bike-sharing services at many public transport stations and physical or virtual mobility hubs. In the project, we aim to develop a data-driven planning model for different infrastructure types to generate efficient cycling infrastructure networks for different user types. Comparing the resulting networks highlights the various constraints during network planning and may help to answer questions such as: How does the structure of efficient bike path networks change when explicitly accounting for first- and last-mile demand from intra-city public transport trips? Does the same network equitably serve different user and usage types, such as short-range city trips and long-range commuting including cycling to access public transport stops? Which part of the bike-sharing network should offer electric bikes to enable longer-range cycling trips?

Overall, we aim to provide an automated, data-driven planning tool to support strategic infrastructure design that helps promote multi-modal active mobility to contribute to more sustainable urban mobility.