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Last update: May 2021

SwITCh - Simulating the transition of transport Infrastructures Toward smart and sustainable Cities

Participatory modelling as a tool to help planners and decision-makers adapt infrastructure to future needs and accelerate the transition to a more sustainable city.

Project founded by Agence National de la Recherche (ANR) on Appel à projet Générique (AAPG) 2019 - CE 22: Sustainable mobility and urban systems

Founded for: 2020-2023

Amount of aid granted by ANR: 492 k€

Abstract :

Transport infrastructures play a large part in defining the city of the future, which should be smart, sustainable and resilient. Their management will need to deal with the emergence of novel technologies (i.e. autonomous cars, Internet of Things), the apparition of novel modalities (hoverboard, etc), and changes of practices (increase of multi-modality, electric bicycles, shared cars). These aspects could favour and accelerate the transition to the city of the future with positive social, environmental and economic impacts, in order to address foreseen trends (climate change and new requirements in terms of pollution, security, and global costs).

The SwITCh project seek to integrate a large variety of urban transport modalities (private car, walk, tramway, bicycle, etc.) and associated infrastructures (pavement, tram track, bicycle path, etc.). It aims to support decision-making for urban planning by simulating the gradual introduction of disruptive innovations on technology, usage and behaviour of infrastructures. Achieving such an objective requires providing a model that is able to assess the impact of these innovations on several key indicators related to mobility, user satisfaction and security, economic costs, and air pollution. It requires a holistic vision of urban transport to avoid indirect consequences of choices or rebound effect (e.g. a solution improving air pollution but reducing security). The model must include current and future infrastructures and modalities, and consider the transition process between current and future situations. We do not provide an a priori list of potential innovations; some of them are already considered (e.g. autonomous car, smart infrastructures, car sharing, etc.), but others will appear from the WP1. Being able to consider a large variety of disruptive innovations and indicators requires a high flexibility of the model; this issue will be at the centre of the modelling process.