Project description
Making the most of data for a better future of mobility
The constantly changing mobility ecosystem requires making the most of data utilisation to shed light on the effectiveness and impact of certain mobility technologies, and the citizens' mobility needs. The EU-funded nuMIDAS project will provide insights on what methodological tools, databases and models are required for the successful integration of all disruptive mobility solutions with the designs of policymakers. Moreover, it will explore how existing ones need to be adapted or augmented with new data. Validating the project's results within a selection of case studies in pilot cities, with varying characteristics, nuMIDAS aims to provide a tangible and readily available toolkit for various applications.
Objective
The mobility ecosystem is rapidly evolving, whereby we see the rise of new stakeholders and services. Examples of these are the presence of connected and automated vehicles, a large group of organisations that rally to establish various forms of share mobility, with the pinnacle being all of these incorporated into a large Maas ecosystem. As these new forms of mobility offerings start to appear within cities, so do the new ways in which data are being generated, collected, and stored. Analysing this (Big) data with suitable (artificial intelligence) techniques becomes more paramount, as it leads to insights in the performance of certain mobility solutions, and is able to highlight (mobility) needs of citizens in a broader context, in addition to a rise in new risks and various socio-economic impacts.
Successfully integrating all these disruptive technologies and solutions with the designs of policy makers remains a challenge at current. let alone being able to analyse, monitor and, assess mobility solutions and their potential socio-economic impacts.
nuMIDAS bridges this (knowledge) gap, by providing insights into what methodological tools, databases, and models are required, and how existing ones need to be adapted or augmented with new data. To this end, it starts from insights obtained through (market) research and stakeholders, as well as quantitative modelling. A wider applicability of the project’s results across the whole EU is guaranteed as all the research is validated within a selection of case studies in pilot cities, with varying characteristics, thereby giving more credibility to these results. Finally, through an iterative approach, nuMIDAS creates a tangible and readily available toolkit that can be deployed elsewhere, including a set of transferability guidelines, thus thereby contributing to the further adoption and exploitation of the project’s results.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- natural sciencescomputer and information sciencesartificial intelligence
- natural sciencescomputer and information sciencesdatabases
- natural sciencesbiological sciencesecologyecosystems
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Programme(s)
Funding Scheme
RIA - Research and Innovation actionCoordinator
3010 Leuven
Belgium
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.