Cycling Analytics for Urban Environments: from vertical models to horizontal innovation - Carvalho, Carlos Eduardo Tinoco (2022)
The full potential of ITS can only be achieved in a global scale and combining the efforts and the knowledge of multiple entities. This is also true for the current efforts towards the application of data, communications and services, to improve cycling and its integration into general mobility systems. The currently prevailing paradigm is based on disperse and self-contained custom processes, which fail to promote distributed and open innovation. These models are hard to reproduce, generalize, recombine or improve outside the context in which they were originally implemented. A digital platform strategy might offer a viable and scalable way to support convergence between multiple models and promote their usage as shared references for cycling ecosystems. In this work, we aim to validate our assumptions about the limitations of current development paradigms and ana-lyse the extent to which a platform strategy could offer a fundamentally different approach to address those limitations. To validate the problem and uncover generalisation opportunities, we study 3 cycling mobility models and make an initial analysis of how the general principles of digital plat-forms could be applied as a general framework for a new type of solution for cycling analytics. The results confirm a high potential for horizontal features and outline a set of key design principles for the development of a digital platform strategy for cycling analytics. This should constitute a major contribution to inform the development of a new generation of cycling plat-forms for urban environments.