NEWS

22. June 2021

Plausibility checks of sensors: Particularly efficient in networks

The more sensors are integrated in a network such as Providentia++, the easier it is to find errors. Intel has developed a plausibility check for the roadside infrastructure monitoring sensors. Researcher Dr. Florian Geißler on identifying and excluding bad measurements.

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30. April 2021

Traffic: Digitalizing like a real-time company

The more traffic is digitalized, the better accidents and traffic jams can be prevented. Real-time decisions have long been established in companies. What can we learn from the world of business? A commentary by Prof. Alois Knoll.

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30. April 2021

How artificial intelligence recognizes objects and looks into the future

What vehicles are on the road, where they are likely to go, and when they will probably change lanes: Artificial intelligence sifts through gigantic amounts of data in fractions of a second, providing new insights into traffic and creating a basis for value-added services.

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What does Providentia stand for?

Providentia is a research project that has been funded by the Federal Ministry of Transport and Digital Infrastructure (BMVI) since early 2017. Since early 2020, it has been continued under the name Providentia++ with the Chair of Robotics, Artificial Intelligence and Real-time Systems at the Technical University of Munich’s Department of Informatics serving as consortium leader. The project’s goal is to research the flow of information between vehicles and infrastructure along the A9 highway extending into the urban area, to create a digital twin of the current traffic situation, and from this to develop value-added services.

What research papers have already been published?

August 13,2020

C-V2X: Architecture for deployment in moving network convoys

Reliable V2X communication is crucial for the development of cooperative intelligent transportation systems (ITS) – and for improving traffic safety and efficiency. A research topic of Providentia++: The approach of moving network convoys.

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August 27,2020

Auto-calibration of radars and cameras for ITS

Most intelligent transportation systems use a combination of radar sensors and cameras for the vehicle perception. Auto-calibration of these types of sensors is complex. This publication proposes a data-driven method based on neural networks.

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August 20,2020

Providentia: Validation of intelligent infrastructure systems

How can aerial image analysis be used to validate intelligent infrastructure systems, and how can this benefit automated vehicles? These questions are the focus of this scientific publication, which takes the Providentia system as an example.

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TECHNOLOGY

Displaying traffic digitally, recognizing vehicles, and transmitting data in real time: These are three of the tasks in store for the technologies. A key role is played by sensors, perception (with object recognition and tracking, as well as data fusion), and 5G wireless technology. In addition to these basic technologies, several other tools serve the visual representation and integration of data, such as the open-source simulator CARLA and the middleware and library framework ROS.

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VALUE-ADDED SERVICES

Whether digital information stems from radar, lidar, or camera systems: The position and speed of trucks, cars, and motorcycles are stored in the digital twin and can be anonymously retrieved and analyzed at any time. Service development is not about monitoring individuals, but rather about analyzing the overall situation, in which many vehicles and the stationary systems along the road communicate with each other and exchange data. New services, application scenarios, and business models are already being planned. Drivers, highway operators, scientists, and car manufacturers all stand to benefit equally from these services in the future.

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RESEARCH AREAS

Reducing huge amounts of data to a manageable size, sending them to the digital twin in real time, and recognizing objects even in the rain or at night: These are among the challenges the researchers in the Providentia++ team are addressing. Research into object recognition, data fusion, communication technology, and the reliability of the overall system are at the heart of Providentia++.

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CHALLENGES

The technical infrastructure is in place. Radars and cameras are in operation; a digital twin has been developed. But some steps toward practical application remain to be taken. The digital twin created by Providentia researchers on behalf of the Federal Ministry of Transport and Digital Infrastructure (BMVI) will soon be used as a prototype in the Providentia++project. But first, the sensor technology must be readjusted, all possible environmental conditions must be mastered, and easy-to-use, modular systems must be created. Only when these hurdles have been cleared will the digital twin be put into practice and produce reliable, usable results.

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The future

“A development toward autonomous vehicles can take place very quickly. That’s how it happened with the Internet. First, two computers were networked together. Decades later came the World Wide Web, and today innovations and new services are created every second.

Professor Dr.-Ing. Alois Knoll

Chair of Robotics, Artificial Intelligence and Real-time Systems

Department of Informatics, TU Munich

Head of Providentia++

“A development toward autonomous vehicles can take place very quickly. That’s how it happened with the Internet. First, two computers were networked together. Decades later came the World Wide Web, and today innovations and new services are created every second.

Professor Dr.-Ing. Alois Knoll

Chair of Robotics, Artificial Intelligence and Real-time Systems

Department of Informatics, TU Munich

Head of Providentia++

PARTNERS

 

(consortium leader)

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