Digital Twins and AI in Road Systems

Artificial intelligence – AI – and digital twins or Digital Twins are two technologies that are revolutionizing the way we perceive and understand the world. Road systems, for their part, are fundamental for the economic, social and cultural development of any country, and therefore require the greatest attention to be up to date with their planning, construction, operation and maintenance.

In this case, we will focus this article on the use of these technologies in road systems, how they can optimize the entire life cycle of a project, improve safety and guarantee efficient mobility of users.

A few days ago Bentley Systems, one of the companies that leads the field of engineering and construction, acquired Blyncsy, in order to expand the solutions and service offering for the planning, design, management and execution of infrastructure projects. Blyncsy is a company that provides artificial intelligence services for transportation operations and maintenance, performing mobility analysis with the acquired data.

“Founded in 2014 in Salt Lake City, Utah, by CEO Mark Pittman, Blyncsy applies computer vision and artificial intelligence to the analysis of commonly available images to identify maintenance problems in road networks”

 The beginnings of Blyncsy laid solid foundations, dedicated to collecting, processing and visualizing all types of data related to vehicular/pedestrian mobility and transportation. The data they collect comes from different types of sensors, capture vehicles, cameras, or applications for mobile devices. It also offers AI tools, with which simulations can be generated that will be transformed into recommendations for optimizing the performance and safety of road systems.

Payver is one of the solutions offered by Blyncy, it consists of cameras with “artificial vision” that are installed in cars and can determine all types of problems that occur on road networks such as potholes or traffic lights that do not work.


 Innovations related to providing solutions that allow people and governments to avoid future problems are key to development. We understand the complexity of road systems, that more than roads, avenues or streets, they are networks that connect and provide benefits of all kinds to a space.

Let's talk about how the use of AI and digital twins complement each other as a powerful tool that allows everyone involved in decision-making to be given accurate and effective information in real time. Digital twins or Digital Twins are virtual representations of structures and infrastructures, and through exact knowledge of these elements it is possible to simulate and detect patterns, trends, any type of anomalies, and of course they offer a vision to determine opportunities for improvement.

With the data found in these powerful digital twins that condense a large amount of information, artificial intelligence could identify critical points of road systems, perhaps suggest better traffic routes where vehicular traffic can be improved, increase network security road or minimize in some way the environmental impact that these structures generate.

Digital twins of highways can be created, for example, that integrate all the information about their material characteristics, temperature, amount of traffic and accidents that have occurred on that road. Taking this into account, different types of scenarios are analyzed to avoid more accidents or create channels so that traffic jams are not generated.

Currently everything is based on planning, design, management, operation, maintenance and information administration systems that facilitate the work of all those involved in construction projects. The fusion of both technologies provides greater transparency of what works and what does not, greater traceability, confidence in data acquired directly from the source and better policies for cities.

Everything mentioned above poses possible challenges that require adequate regulations for their implementation and use. For example, governments must guarantee the quality, interoperability and reliability of all the data that is constantly feeding digital twins and protect them from any type of attack.


These technologies can be applied to the road sector in various ways, from planning and design phases to construction, monitoring and maintenance. In the planning phase, Artificial Intelligence is used to analyze traffic, mobility, and the environmental impact produced by continuous traffic, and provides data that allows generating proposals for road expansions.

Regarding design, we know that digital twins are the faithful copy of what was built in real life, and that integrated with Artificial Intelligence they allow us to create optimal designs. All this, taking into account established criteria, regulations and standards, to subsequently similarize the behavior of the structures with the digital twin.

In the construction phase, both technologies are used for the optimization and management of resources, and to advance the schedule established in previous phases. Digital twins can be used to monitor the progress and status of the work, as well as to detect any type of lack or errors.

When we get to the Operation, we could say that AI optimizes the road system, a correct integration could help reduce carbon emissions into the atmosphere. Digital twins indicate the performance and capacity of the road infrastructure, being able to determine if they require preventive, corrective or predictive maintenance, extending the useful life of the system.

 Now, we will show just a few examples of how AI and digital twins can transform road systems and offer innovative solutions to current and future transportation challenges.

  • Indra, one of the most important technology and consulting companies in Europe, began the creation of a digital twin of the A-2 Northeast highway in Guadalajara, aimed at reducing accidents, increasing capacity and availability of roads and will allow improving the performance of State agencies in the event of any event,
  • In China and Malaysia the company Alibaba Cloud developed an AI-based system for detecting traffic status in real time, with which it can control traffic lights dynamically. This system reduces accidents and helps users have better travel times and save fuel. All this is contemplated in your project City Brain, whose objective is to use AI and Cloud Computing technologies that will allow generating analysis and optimizing public services in real time.
  • Likewise, Alibaba Cloud has alliances with Deliote China for the creation of fully autonomous vehicles in China, estimating that by 2035 China will have more than 5 million autonomous vehicles.
  • About us ITC – Intelligent Traffic Control from Israel, develops a program in which all types of data can be stored in real time, captured by surveillance sensors on streets, avenues and highways, manipulating traffic lights in case of traffic jams.
  • google waymo It is a travel service with autonomous vehicles operated through AI, available 24 hours a day, in multiple cities and under the premise of being sustainable. These unmanned vehicles have a large number of laser sensors and 360º peripheral vision. Waymo has traveled billions of kilometers, both on public roads and in simulation environments.

“Data to date indicates that the Waymo Driver reduces traffic accidents and related deaths where we operate.”

  • Smart Highway Roosegaarde-Heijmans - Holland. It is a project for the establishment of the world's first glow-in-the-dark highway, thus ushering in the era of smart highways. It will be a sustainable, low-consumption road that is illuminated with photosensitive and dynamic paint that is activated with lighting sensors close to it, completely changing the conventional design of land roads worldwide. The premise is to create roads that interact with the driver, with special lanes for electric vehicles where they are fully charged when driving on them.
  • StreetBump. Since 2012, the Boston City Council implemented an application that notifies authorities about the existence of potholes. Through this application, users can report any potholes or inconveniences on the roads, it integrates with the GPS of mobile phones to detect vibrations and location of the potholes.
  • Rekor One With the incorporation of the Waycare platform, they create Rekor One Traffic and Rekor Discover. Both use artificial intelligence and data capture devices that transmit high-resolution videos, in which traffic can be seen in real time and the vehicles traveling on the roads can be analyzed.
  • Sidescan®Predict Brigade, is a system that integrates artificial intelligence for collision prevention. It collects a large amount of data in real time, such as distance, vehicle turning speed, direction and acceleration. It is designed for heavy vehicles, since their weight and the damage they can cause is much greater than that of a conventional vehicle.
  • Huawei Smart Highway Corps. It is a smart road service and is made up of 3 scenarios based on artificial intelligence and Deep learning: intelligent high speed, smart tunnels and Urban traffic governance. For the first of them, it focuses on consultancies where all types of scenarios are evaluated using applications, data integration and technologies to facilitate the implementation of smart roads. For their part, smart tunnels have electromechanical solutions for their operation and maintenance based on IoTDA, including emergency links and holographic messages so that drivers can be aware of any inconvenience on the road.
  • Smart Parking from the Argentine company Sistemas Integrales: uses artificial intelligence to facilitate vehicle parking in cities. The system detects free and occupied spaces using cameras and sensors, and provides drivers with real-time information on availability and price.

We could then say that the combination of AI and digital twins offers multiple benefits for traffic management and road systems, such as:

  • Improve mobility: by reducing traffic jams, travel times and polluting emissions, by promoting the use of public transport and shared mobility, by adapting transport supply and demand to the needs of users and by facilitating access to information on the traffic.
  • Improve security by preventing and reducing accidents, alerting drivers and pedestrians of possible risks, and promoting coordination between emergency services, facilitating assistance to victims.
  • Finally, improve the eficiency by optimizing the use of resources, reducing operating and maintenance costs, increasing the useful life of infrastructure and vehicles and increasing the quality of service.


In addition to the digital infrastructure that must be implemented to establish good communication and integration between technologies, parameters and standards must also be defined that guarantee interoperability between systems. Likewise, connectivity and cybersecurity play a key role in achieving this.

It has been said that artificial intelligence could eliminate human labor, but it will still require trained personnel to keep the systems working efficiently. They must receive constant training that is on par with technological innovations. In addition to the above, it could be said that a legal and ethical framework is necessary that promotes and guarantees the correct use of data and sustainability.

The application of both technologies would significantly improve the lives of users, with this there would be greater reliability in road systems, creating comfort, reduction of accidents and a more harmonious spatial dynamic with the immediate environment. Both challenges and opportunities must be taken into account and strategic visions and transcendent business models offered.

In conclusion, artificial intelligence and digital twins are two technologies that are transforming traffic management in an innovative and effective way, both allow us to create more intelligent, sustainable and inclusive cities, where traffic is an element that makes life easier and not more difficult. of people.

Golgi Alvarez

Writer, researcher, specialist in Land Management Models. He has participated in the conceptualization and implementation of models such as: National Property Administration System SINAP in Honduras, Management Model of Joint Municipalities in Honduras, Integrated Cadastre-Registry Management Model in Nicaragua, Territory Administration System SAT in Colombia . Editor of the Geofumadas knowledge blog since 2007 and creator of the AulaGEO Academy that includes more than 100 courses on GIS - CAD - BIM - Digital Twins topics.

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