Pilot city: Barcelona (Spain)

The Barcelona Metropolitan Area has a population of 3.2 million inhabitants in a 636 km² area, with a high demographic density that reaches 50,000 people per km² in Barcelona’s city centre (it is one of the largest metropolitan areas in Europe). The modal share of walking is notably high in the city centre (46 %) and the use of urban public transport has been rising progressively.

However, in a metropolitan vision where the public transport and private mobility services offer is lower, the car participation in the modal share is very high, creating several externalities such as congestion, poor air quality, and a social welfare loss. Indeed, there is a lack of mobility options from the travels from/to outside Barcelona city centre that leads to higher user of car in the modal share. This situation leads to high congestion levels, poor air quality, and other negative externalities of private motorised mobility. In January 2020, the low-emission zone came into force and, at the same time, the Barcelona metropolitan area experienced a growth of mobility services, with the objective to promote a behaviour change towards sustainable mobility.


Within this project, a pilot will be developed as a business intelligence process to identify the technical and methodological needs to use available mobility data from conventional services such as bus lines and road traffic, cross-referenced with new services such as on-demand buses, electric buses, park & ride, mobile apps with mobility information or for sharing services (public bike-sharing and private moto-sharing operators) among other emerging mobility solutions.

The nuMIDAS project will be used to create a standard characterisation model to integrate data from third parties in order to minimise technical efforts required for the data processing flow.

The nuMIDAS toolkit will provide a dashboard with all the information available with the following objectives:

• to expand the knowledge about end-users and their mobility patterns, • improve mobility planning, • obtain key performance indicators on level of services, and improve the information available to the users.