Understanding travel between the city and its surrounding areas to design more efficient mobility:
the Padua case study
THE PROJECT
Motion Analytica participated in a project to analyse mobility patterns across the 19 municipalities that make up the .
Using mobile network data provided by Vodafone Italy, it was possible to analyse people’s movements, generating valuable insights to support the development of the city’s new Sustainable Urban Mobility Plan (SUMP).
CLIENT
Comune di Padova
MERCATO
Travel & Transportation: Urban Mobility
ANALYSIS
Urban mobility and presence analysis
MAIN RESULTS
01.
Mobility behaviour analysis
The analyses provided a detailed understanding of people’s travel habits, identifying the main mobility patterns across the Metropolitan Area of Padua.
02.
Mobility Flow Mapping
The Origin/Destination matrices enabled the identification of the main travel corridors and highlighted the areas where improvements to the local transport network were most needed.
03.
Support for urban mobility planning
The results, delivered through interactive dashboards, zoning maps and filterable databases, supported the development of the city’s Sustainable Urban Mobility Plan (SUMP), contributing to the design of a new tram line.
THE ANALYSIS
Over the course of 4 months (february-may), we analyzed:
2.8 million users
46 total areas
Approx 140 million trips
Users were categorized into 3 main categories:
residents in the municipality of Padua
Italian visitors (by province of residence)
foreign visitors (by nationality)
Finally, the data were divided into time aggregations that can be filtered according to specific needs:
monthly aggregations
daily aggregations (with distinction between weekdays and holidays)
aggregations in 4 main time slots with respect to peak and normal traffic
CONCLUSIONS
The purpose of the project was to reconstruct people’s travel flows through origin-destination matrices and support the update of the Sustainable Urban Mobility Plans (SUMP) developed by the municipality of Padua.
Mobile phone data, that were analyzed and integrated with other heterogeneous sources, were found to be crucial in revealing the various travel needs of inhabitants, both within the metropolitan and suburban areas.
The information collected has been aggregated in different groups and presented through interactive dashboards that enable an in-depth understanding of the phenomenon and support decision making.