AI and Big Data: the technologies that will allow transport to save 500,000 million in time and fuel

Indra has developed projects with these technologies for land, air, rail and public transport traffic, among others

MADRID, 7 May. (EUROPA PRESS) -

The rise of artificial intelligence (AI) and Big Data has the capacity to revolutionize the transport sector with savings in time and fuel that could amount to 500,000 million dollars (453.47 million euros), according to OECD data. .

In a European perspective, a 10% improvement in the efficiency of the sector would mean savings of 100,000 million euros, according to data from Alice ETP, collected by Indra, one of the companies working on the digitization of the sector.

Transport is one of the strategic sectors for the development of the economy, both in Spain and globally, and also has an impact on the daily lives of citizens.

According to ICEX data, logistics and transport account for 10% of Spain's GDP, with more than one million jobs and close to 200,000 companies linked to the sector, while in the EU they account for 15% of GDP and they employ 11.2 million people.

"The irruption of AI in traffic management systems has been a true revolution in terms of efficiency, safety and sustainability, due to its contribution to reducing travel times, improving road safety, saving costs and reducing polluting emissions", explains the coordinator of Mobility innovation projects at Indra, Mauro Gil.

Gil has highlighted that, if their use becomes widespread in a sector as traditional as transport, these technologies will have a substantial impact both on the industry and on people's daily lives.

In this sense, according to the report "Use of artificial intelligence and big data in Spanish companies", published this year by the National Observatory of Technology and Society of the Ministry of Economic Affairs and Digital Transformation, only 9.1% of companies of Spanish logistics and transport use AI solutions and 24.6% make use of big data.

For this reason, a greater penetration of these technologies is key so that the revolution that they can bring to the sector materializes and reaches society.

The technological engineering company Indra has its own transport solutions with the most advanced technologies and has led and is leading several of the most advanced AI projects in the sector.

Thanks to this technology, the company has managed to move from a preventive operating model to a more predictive one and has managed to reduce polluting emissions by 25%, maintenance interventions by 10% and operating costs by 34%. .

Thus, a specific application of AI by the company is the In-Mova Traffic technology, which monitors and manages traffic in tunnels and open-air roads around the world. This allows comprehensive control of infrastructure and traffic with a high degree of automation.

The solution has Automatic Incident Detection (DAI) technology, equipped with artificial intelligence, which integrates, processes and analyzes the information from the cameras installed throughout the works to facilitate a rapid and largely automated reaction to any incident.

Indra has equipped the control center that integrates the management of Transurban highway assets in the Australian state of Queensland with this technology, which include the three largest tunnels in the city of Brisbane, where artificial intelligence algorithms make predictions based on the traffic data.

Likewise, the company's occupant detection system, based on artificial vision and 'deep learning', makes it possible to automatically detect, in real time, in a non-intrusive way and with high reliability, the number of occupants (front and rear) of the vehicles.

Indra is already implementing this advanced technology in countries such as the United States, in several express lanes in northern Virginia and on the I-66 access highway to Washington, or Israel, in the new fast lanes of Highway 20 that connects Tel Aviv with the rest of the country.

This technology allows progress towards advanced mobility models, such as access control to cities in high-occupancy lanes or dynamic pricing systems, in which the amount of the toll varies according to the number of occupants, the type of vehicle or emissions .

In the field of public transport, Indra has deployed a pilot in the north of Madrid with data from the bus operator InterBus, in which it has been possible to predict the sale of tickets and passengers or possible failures in the system based on descriptive models. generated from the data.

Likewise, in the field of predictive railway maintenance and logistics management, the company has also conducted projects on freight trains using artificial vision algorithms to identify wagons, containers and plates of dangerous goods from images and 'RFID tags'.

In the case of air traffic, Indra is also working on advanced innovation projects that exploit these new digital technologies to make predictive models of passenger flows in airport terminals, within the framework of the SESAR innovation macroprogram.

In addition, it has also developed algorithms to optimize the 'turnaround' -the process of preparing an aircraft for takeoff after its arrival at the airport-, in order to reduce the time that aircraft are on the runway.

In all of these projects, Indra has been able to predict vehicle demand, generate probabilistic accident rate models, predict infrastructure degradation or identify types of travelers at airports and predict their behavior, among other advantages.

One of Indra's most innovative projects, in collaboration with Cintra, is CRIS (Central Road Information System), a platform that automatically and in real time recommends to operators the information that would be good to share both with vehicles connected through vehicular communications, such as traditional without connection through variable messaging panels.

This solution, which takes advantage of big data and artificial intelligence and can reach a processing capacity of 10 messages per vehicle and second for traffic of more than 200,000 vehicles per day, is fed by data from all types of sensors and the connected cars themselves and is already being deployed on the I-66 Outside the Beltway access to Washington.

All these developments show that AI is the great ally of transport to face its great challenges of the future: to be more autonomous, intelligent, efficient, safe, accessible and sustainable.

There is more and more data and AI allows it to be processed and managed at a speed never seen before, which allows transport to move from a preventive model to a predictive one while optimizing and automating all its processes.

"AI is becoming more accessible, which means that every day more companies in the industry are beginning to apply it, facing their great challenges of the future. The objective must be to reach a much more globalized and integrated transport, which helps for the different modes of transport to 'communicate' with each other", concludes the Mobility innovation project coordinator at Indra.