The acceleration of AI opens new avenues for the intelligent management of urban mobility

In this universe of public and private transportation management, of intelligent transportation systems (ITS), IBM has recently announced the application in Madrid, together with the technology consulting company Virtual Desk, of generative AI in the EMT (Municipal Transport Company), to improve urban mobility and elevate the user experience, in a safe and scalable framework (the day with the highest demand in 2024 was May 14, with 1,804,271 travelers). A technological performance to manage a fleet of 2,100 buses and the Bicimad public bicycle system, which moves more than 454 million travelers per year, with 227 bus lines (more than 4,000 km.)

IBM’s partner specialized in digital transformation solutions has developed this application to transform the way customer queries and requests are managed, with a first phase based on watsonx, IBM’s business Data and AI platform. The new application automatically classifies queries, recognizing their relationship with Bicimad stations or bus lines, and proposes a standard response for EMT agents. Virtual Desk is also the company responsible for the construction of the information system for the Public Transport Card of the Community of Madrid (TTP), which manages more than 7 million trips daily.

Virtual Desk has products such as Ai4Transportation, based on Big Data and AI technologies that offers data integration and management; advanced analytics; data availability and visualization; an environment for building new analytical applications; process optimization, security and data governance. A whole ‘suite’ of solutions to work on the demand predictiongeneration of multimodal ‘origin-destination’ matrices, identification of transport use patterns, etc., in urban scenarios in which companies such as Amazon have also invested in AI solutions to optimize processes in this regard through Amazon Operations Innovation Lab.

«The implementation of AI in the Madrid EMT (says Fernando Suárez, IBM software director) demonstrates how cities can address these challenges with advanced technological solutions. Not only does it speed up the management of queries, but it allows cities to use their resources more efficiently and is a solution that can be applied to other cities seeking to optimize their transport systems, face urban challenges with an innovative approach and offer a better service to its citizens.

These solutions are added to the initiatives launched by the Madrid City Council (Urban Planning, Environment and Mobility Area), which manages traffic in real time through 56 cameras with AI, with additional baggage to analyze in recent years. two and a half years of data contained in 510,000 hours of video captured from the different measurement stations.

These cameras are installed in key axes for the city’s mobility such as the streets of Alcalá, Princesa, Camino de los Vinateros, Arcentales, Joaquín Costa or Plaza de España. Added to this is the measurement of pedestrian traffic: Gran Vía broke its capacity record recorded on the weekends of ‘Black Friday’ and the Constitution Bridge: during those six days (November 29 and 30 and 1, 6 , December 7 and 8), and nearly 1.4 million people walked through it. Measures that are added to those undertaken by Metro Madrid to automate and make its trips more efficient in the face of enormous passenger demand.

This process of coordination, of coexistence between vehicles, traffic lights and pedestrians is already common in other Spanish cities such as Barcelona, ​​Seville, Valencia, Bilbao or Malaga. And in cities like San Francisco, where sensors are used to adjust traffic lights according to traffic conditions in real time, or Vienna, with solutions such as Kapsch TrafficCom to optimize the flow of vehicles. In the case of Nordic cities, such as Stockholm or Copenhagen, the large number of cyclists is taken into account, so there is special technological ‘surveillance’ on bike lanes.

in real time

Indra highlights its advances in AI, 5G, Big Data and ‘digital twins’ applications “with the objective (the company points out) of understanding mobility patterns in public transport through real-time data processing to provide alternatives, information on services or possible incidents, or integrating all the sustainable transport options available to the user.

With examples such as obtaining one of the largest ticketing contracts in the world to modernize the public transport ticketing system in Ireland, offering travelers on the same platform to pay for everything from traffic alerts, buses, to information about electric vehicle chargers. And use cases such as its occupant detection system (Davao) with AI and ‘deep learning’ “for intelligent and more efficient control of access to cities to implement fairer and more sustainable mobility policies, contributing to the use of public transportation »: automatically detects the number of people traveling in a car and makes it possible to calculate emissions per passenger to ‘reward’ those vehicles with the lowest emissions rate per occupant.

In the field of startups that already contribute to this technological deployment, Ibon Arechalde, CEO and co-founder of Asimob, highlights how their work focuses on the Vision Zero objective established by the European Commission: «Our purpose is to improve Road Safety with a ethical use of technology, the generation of quality local employment and the development of solutions with real impact around the world.

Its AI model and software applications are also applied in urban contexts: «One of the great challenges is to reduce traffic accidents in urban areas. The adoption of new, vulnerable transport, such as scooters or electric bicycles, generates new dangerous situations, as these vulnerable vehicles coexist with much heavier ones and with pedestrians, also vulnerable. In fact, reducing speed to 30 km/h in cities has not made these accidents disappear.

Safe, sustainable

Its ‘Urban Autonomous Inspector’ has the triple objective of improving the efficiency of street and highway maintenance, improving Road Safety and facilitating the adoption of autonomous vehicles. «Based on artificial and sensory vision (Arechalde points out), it allows inventory and analysis from any vehicle of the state of all the elements that make up the streets and highways on which that vehicle travels. In this way, those responsible for the infrastructure receive information about all the defects found in traffic signage, road markings, protection barriers, lighting or the condition of the pavement. A solution that allows this information to be combined with the geometric data of the infrastructure to detect risk points, before they become ‘black spots’.

Regarding ongoing research, institutions such as Imdea Networks, an entity dependent on the Community of Madrid, has various projects, several of them with European funds, with special focus on the ‘digital highways’ of 5G and the upcoming 6G. «The Daemon projects (2020-2024), funded by the EU, and its continuation Origami (2024-2026) investigate (highlights researcher Marco Fiore), the next generation of 6G mobile networks, focusing on the automated management of these future infrastructures. of communication. Specifically, the projects develop new network architectures and original AI models that promote the native integration of this AI in 6G systems and allow them to be self-managed with minimal human intervention. Support for very diverse classes of service and near-zero latency “part of a system (adds Fiore) with 100% reliability and availability, ubiquitous connectivity and high sustainability, with a low energy impact.”

A journey of interconnection

The General Directorate of Traffic (DGT), although it focuses on interurban traffic, shares technological transfer with city councils, provincial councils and CC.AA. This has been the case since DGT 3.0the connected vehicle platform that facilitates the interconnection of all actors in the mobility ecosystem (vehicle manufacturers, navigation service providers, mobility applications, city councils, public transport platforms, fleet management systems, etc.), “to offer real-time traffic information to road users at all times to lead to safer and smarter mobility.” A task for which it has 232 cameras with AI to monitor traffic, make traffic more efficient and reduce accidents as much as possible.