There is a growing recognition that traditional forecasting and decision-making approaches might fall short considering the many uncertainties and complexities facing the development of the transport system. The project Managing deep Uncertainty in planning for Sustainable Transport (MUST), funded by Trafikverket and conducted by KTH ITRL and VTI, aims to explore emerging methods for improving the handling of deep uncertainty in the long-term planning of future transport systems. The core of MUST is to explore, develop, and demonstrate tools and methods grounded in Decision Making under Deep Uncertainty (DMDU) and Exploratory Modeling and Analysis (EMA). These approaches are intended to support a shift towards more robust and adaptable planning methodologies. The project is performed in two phases, with the first phase dedicated to laying a foundational understanding of deep uncertainty in transport planning. This report covers the first phase which has included the following tasks: - A literature review on deep uncertainty and existing decision-making and system analysis methods under such conditions, with a focus on transportation. - A workshop series with Trafikverket identifying transport planning challenges marked by deep uncertainty. - A case study of applying DMDU through a case study on climate policy robustness.