Abstracting Mobility Flows from Bike-sharing systems

Bicycling as a means of transportation in modern cities has grown sig- nificantly in the past ten years. In some regions, the appearance implementation of large-scale bike-sharing systems and improved cycling infrastructure are two of the factors that enable enabling this growth. An increase in non-motorized modes. of transportation makes our cities more human, decreases pollution, traffic, and improves quality of life. In many cities around the world, urban planners and poli- cymakers are looking at cycling as a sustainable way of improving urban mobility. NeverthelessAlthough bike-sharing systems generate abundant data about their users' travel habits, most cities still rely on 20th-century traditional tools and methods for planning and policy-making. Recent technological advances enable the collection and analysis of large amounts of data about urban mobility, which can serve as a solid basis for evidence-based policy-making. In this paper, we introduce a novel analysis analytical method that can be used to process millions of bike-sharing trips and analyze bike-sharing mobility, abstracting relevant mobility flows across an urban area. The specific urban areas. Backed by a visualization platform, this method provides a comprehensive set of analytical tools that can support public policy and mobility planning authorities in making data-driven policy and planning decisions. This paper illustrates the use of the method with a case study of the Greater Boston bike-sharing system and, as a result, presents new findings about that particular system. Finally, an assessment with expert users showed that this method and tool was considered very useful, relatively easy to use, and that they intend to adopt it in the near future.