During European Mobility Week we wanted to look at mobility from a different angle: letting the data tell us how we move.
Over five days we shared on our LinkedIn channel some of the results obtained from information collected during July and August at different points along the A-1 and A-2 motorways.
The starting point is particularly interesting. The Bluetooth sensors used for this analysis were originally installed to monitor emergency parking areas. However, reusing the data they collected has made it possible to explore new questions about hourly and weekly patterns, routes, directions of travel and the length of certain stays.
It is a very concrete example of one of the core ideas behind data spaces: data created for one purpose can take on new value when it is reused to meet other needs.
That said, reusing also means validating. Not all variables offer the same quality or allow conclusions to be drawn with the same level of confidence. Telling a solid pattern apart from a mere hint is also part of the analysis.
Mobility has its own weekly rhythm
The first pattern the data shows emerges when we look at how activity changes over the week.
On both corridors, volume rises on weekdays and falls at the weekend. However, each day has its own particular features.
Saturday records the lowest level of activity, while Sunday behaves differently: there are approximately 70% more return trips than outbound trips.
There is also a recognisable hourly pattern. Activity starts to rise clearly between 6:00 and 10:00 and declines from 19:00.
These behaviours may seem intuitive, but the value of the data lies precisely in making it possible to observe them, measure them and check how consistently they repeat.
Two corridors, two ways of moving
Analysing the data as a whole makes it possible to identify general trends. But separating it by corridor reveals another important conclusion: there is no single pattern of interurban mobility. The A-1 and the A-2 show clear differences throughout the period analysed.
On weekdays, the A-1 records a sharper peak in activity around midday and shows greater variability. The A-2, on the other hand, behaves considerably more steadily for much of the day.
The differences also appear when looking at return trips. On the A-1 the peak is concentrated in the morning, while on the A-2 it clearly occurs around 17:00.
Comparing the two corridors shows why it is important to analyse each context specifically. Two similar infrastructures can respond to very different mobility dynamics.
When does the weekend really start?
The data even shows the moment when travel behaviour starts to change. Comparing Thursday and Friday, the curves begin to diverge at around 14:00 on Friday, and the difference peaks at approximately 17:00. Saturday already shows a completely different pattern.
But the analysis does not only show when journeys take place. For trips that can be followed with enough confidence, it is also possible to estimate how long they last.
The average stay observed is around 3 days on the A-1 and 4 days on the A-2. In addition, more than 70% of stays last between one and six days, while from one week onwards a second pattern appears, associated with longer trips.
Mobility is therefore no longer understood only as a question of volume. Data can also help us analyse when a journey starts, when it ends and how much time passes between the two.
Data also reveals how we travel
One of the last analyses of the week allowed us to look even more closely at the types of journeys observed.
More than half of the vehicles classified as lorries appear at two or more points along the corridor, compared with approximately 7% of conventional vehicles. This is consistent with the greater weight of interurban routes in freight transport.
When the same vehicle appears at different stations during a day, it is also possible to reconstruct part of its route. The analysis identified around 27,000 vehicles passing through four or more stations.
Interesting patterns also appear in the length of certain stops, with concentrations around 45 minutes and 8 hours, times that match the rest periods set for professional road transport.
Data originally collected for another purpose thus makes it possible to put forward new hypotheses and gain a different perspective on how these corridors work.
Reusing data to open up new questions
If we had to sum up the five days of analysis in a single idea, it would be precisely this: reusing existing information can open up new ways of understanding mobility without having to start from scratch.
Over the week we went from asking where the data came from to observing the weekly rhythm of mobility, comparing two corridors, estimating the length of certain trips and studying some patterns related to professional transport.
Above all, the exercise shows the potential of connecting and reusing information to ask new questions.
That principle is also at the heart of DS4MM: creating an environment in which data can be shared and reused to feed new analyses, models and use cases related to mobility.
European Mobility Week is over, but the data still has many stories to tell.
