Many European cities are investigating how to transition to climate-neutral transport systems. Due to the transport system's complexity and uncertainty about the future, identifying drivers and choosing effective policies to make the city more sustainable is challenging. Additionally, the chosen policies need to be supported by relevant actors. This study aims to support the municipality of The Hague in generating robust policies supported by and within the municipality. We build on participatory modeling and decision-making under deep uncertainty to create a novel approach to address this goal. In two workshops, the participants formulated goals and objectives, created Causal Loop diagrams, and identified potential interventions. Using a set of possible futures, the interventions were then stress-tested to evaluate their robustness. By explicitly linking, for the first time, participatory modeling and decision-making under deep uncertainty approaches, the participants could understand the system better and deal with uncertainty. Participants gained insight into systemic complexity and methods to deal with it, the inter-relatedness of interventions and their effects, and a shared understanding of the problem and its scope. This study demonstrates the potential of a novel approach to generate supported robust interventions to achieve the goal of a climate-neutral transport system.

@en

Visioning has been widely adopted in transport planning as a method to support explorations of possible future transport systems over a long time horizon. There are vast variations in how visioning is applied but given a clear association between visions and the long-time perspective, it is unclear how these processes handle uncertainty surrounding the resulting visions and their implementation. This study reflects on previous visioning processes by systematically reviewing the scientific publications on participatory visioning in passenger transport. The review identifies possible improvements contributing to a systematic approach that produces concrete visions and actions to deal with uncertainties surrounding the vision and its implementation. We address these improvements by proposing a robust and generative visioning framework, which combines the generative approach in Appreciative Inquiry (Ai) and methods to handle uncertainty in the Dynamic Adaptive Planning (DAP). The framework is illustrated in a case study of the Southwest area of the Dutch city of the Hague that involved over 50 participants in a survey and two workshops. The process produced a vision for the mobility system of the area, a set of measures to realize it (i.e. pathways), and concrete actions to ensure that the pathways are robust against different futures that can affect the implementation. The approach can help planners, policymakers, and researchers in designing a visioning process that helps participants to better appreciate the temporal dimension of the visioning process and improves their awareness regarding the need to safeguard policy interventions against possible impacts of (un)certain future events.@en

Mobility as a Service (MaaS) is a recent innovative transport concept, anticipated to induce significant changes in the current transport practices. However, there is ambiguity surrounding the concept; it is uncertain what are the core characteristics of MaaS and in which way they can be addressed. Further, there is a lack of an assessment framework to classify their unique characteristics in a systematic manner, even though several MaaS schemes have been implemented around the world. In this study, we define this set of attributes through a literature review, which is then used to describe selected MaaS schemes and existing applications. We also examine the potential implications of the identified core characteristics of the service on the following three areas of transport practices: travel demand modelling, a supply-side analysis, and designing business model. Finally, we propose the necessary enhancements needed to deliver such an innovative service like MaaS, by establishing the state of art in those fields.@en