UrbanMOVES will develop advanced transport models to quickly select the most attractive, efficient, and tailored shared mobility systems for each city to reduce delays and pollution in rapidly growing cities. Travellers’ preferences and choices will be integrated into efficient aggregated traffic models that reduce the complexity of traditional models. This is possible by simplifying the road network representation and capturing accurate traffic congestion dynamics. A new tool for quick comparison of mobility systems will enable tailored policy recommendations and new scientific understanding of the role of key city characteristics on optimal shared mobility. UrbanMOVES paves the way for sustainable mobility.

De afgelopen jaren zijn vele ‘losse’ pilots en living labs gestart op het vlak van duurzame stedelijke mobiliteit. Om tot structurele en innovatieve oplossingen te komen is meer nodig! Het SUMMALAB verbindt verschillende initiatieven en labs in verschillende steden. Het SUMMALAB bundelt kennis, data, modellen en stakeholders en biedt een basis voor succesvolle co-creatie, experimenten/pilots, opschaling en implementatie van maatregelen om tot duurzame, veerkrachtige stedelijke mobiliteitssystemen te komen. Het SUMMALAB is een platform voor verdiepend, integrerend, vergelijkend en toegepast onderzoek. Het maakt datagedreven analyse en modellering mogelijk om de effecten van en de interactie tussen interventies te kunnen onderzoeken.

Increasing urbanisation and worsening congestion in all modes of transport has lead cities to experiment with innovative solutions for passenger and freight transport using less vehicles to transport more people and higher freight volumes, using less space, with less emissions. SUMMALab (Smart Urban Mobility MetA Lab) connects and supports such experiments with tools focusing on ‘business models’, ‘technical monitoring’, ‘mobility and environmental impacts and inclusiveness’ and ‘scalability’ and develops transport models that provide insight into the impacts of innovative solutions when applied in combination, at higher penetration rates and for larger areas. SUMMALab facilitates cross-location learning and accelerates scaling up.

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