In FOMO, Urban Sharing AS, in collaboration with NTNU, Entur and Oslo City Bike will create a data-driven, optimization-based decision support tool for managing an adaptive and responsive urban micromobility system. By merging deep knowledge about operations research with data and experience from bike sharing systems, we will develop state-of-the-art methods to support tactical and operational planning. Objectives include predictive asset rebalancing, predictive maintenance and management of multiple assets in one platform. The models and methods will be extensively tested on real transport systems using a novel technical framework that allows us to collect data and statistics to evaluate and assess them. This closeness between research and a real transport system narrows the gap between theory and practice and shortens the path from research to commercialization.
Project leader: Kristian Brink