Bike-sharing is one of the several emerging modes that will be explored in MOMENTUM, thus we are glad to share that our colleagues from the Technical University of Munich (TUM) have published an open-access research on the demand forecasting for bike-sharing systems in New York City. Our experts were able to apply machine learning techniques, by combining available information related to temperature and precipitation with overall 17 million trips with shared bikes around New York City. The method resulted in a stunning 75% accuracy of predicting the demand pattern of New York City bikes. MOMENTUM will explore more such models for the emerging transport solutions.

If you would like to learn more, you can access the freely available research on page of the Journal of the Transportation Research Board on the SAGE Journals platform.