All transport operations, whether passenger or freight, involve complex movements of vehicles, people or consignments. In a connected economy, all this activity generates data yet barely a fifth of EU transport organisations make good use of digital technologies to identify patterns and trends that could improve their operations.
The key concepts are big data and artificial intelligence, says Rodrigo Castiñeira, of Indra, a leading global technology and consulting company, that coordinated the EU-funded Transforming Transport (TT) project.
‘In a nutshell, big data is how you collect, process and store data,’ he explains. ‘Artificial intelligence is how you exploit this data, the intelligence – algorithm, model, etc. – that extracts information and knowledge.’
The EUR 18.7-million project employed several established technologies – notably predictive data analytics, data visualisation and structured data management – not previously widely applied in the transport sector.
These solutions were trialled in 13 large-scale pilot schemes for smart highways, railway maintenance, port logistics, airport turnaround, urban mobility, vehicle connectivity and e-commerce logistics.
Knowledge in action
Data came from operational efficiency metrics, customer feedback, arrival and departure times, freight delivery statistics, waiting times at transport hubs, road traffic records, weather data, traveller habits and maintenance downtime records among others.
‘TT was knowledge in action,’ says Castiñeira. ‘We deployed the pilots in an operational environment. We used real-time and live data in most of the pilots. We involved real end-users, so we were talking to all the transport authorities, railway operators, and so on.’
The scale of project was astonishing, with 49 formal partners in 10 countries over a 31-month period but drawing in an estimated 120 organisations of all sizes across Europe.
Although the pilots were self-contained, they were assessed by common criteria for impacts on operational efficiency, asset management, environmental quality, energy consumption, safety and economy.
Among the many headline benefits from TT were accurate road-traffic forecasts up to two hours ahead, railway maintenance costs cut by a third, delivery truck journey times reduced by 17 % and airport gate capacity boosted by 10 %.
Castiñeira says improving the sustainability and operational efficiency of transport infrastructure, especially in the rail and road sectors, can help operators cope with networks that are reaching capacity. ‘By using these technologies they could fully optimise resources and infrastructure.’
The value of big data
Big data can also reveal opportunities for new business models, such as retail provision in airports informed by data on passenger circulation.
Travellers benefit, too, from smoother traffic flows and fewer queues and delays. ‘So all this leads to a much better customer experience just with technology while you optimise the investment in infrastructure,’ he says.
‘We demonstrated the value of big data to these transport end-users so now that the project is over some of these operators are still using the TT tools. I think that’s a very relevant and important result.’
Partners have identified 28 exploitable assets that can be commercialised and 40 that could also become exploitable and even lead to patent applications.
Castiñeira notes that participants are now more aware of what big data can do and intend to specify data collection when planning new transport projects. Data is now seen to have a value it did not have before especially when shared with others. ‘When you share your data it’s a win-win situation,’ he says. ‘You win because you get additional data and then knowledge and the other party can also get added value from your data.’
TT was one of the ‘lighthouse’ projects of the European Commission’s Big Data Value public-private partnership.