Semi-Automated Location Planning for Urban Bike-Sharing Systems

Bike-sharing has developed into an established part of many urban transportation systems. However, new bikesharing systems (BSS) are still built and existing ones are extended. Particularly for large BSS, location planning is complex since factors determining potential usage are manifold. We propose a semi-automatic approach for creating or extending real-world sized BSS during general planning. Our approach optimizes locations such that the number of trips is maximized for a given budget respecting construction as well as operation costs. The approach consists of four steps: (1) collecting and preprocessing required data, (2) estimating a demand model, (3) calculating optimized locations considering estimated redistribution costs, and (4) presenting the solution to the planner in a visualization and planning front end. The full approach was implemented and evaluated positively with BSS and planning experts.