Traffic: Added value by big data

More than one petabyte data is created week by week on the Providentia++ test field. They are needed as to distinguish cars from motorcycles and bicyclists, to recognize maneuvers, to analyze accidents and to simulate traffic.


Traffic: Added value by big data

23. November 2021 A huge amount of data is needed as to distinguish cars from motorcycles and bicyclists, to recognize maneuvers, to analyze accidents and to simulate traffic.

Software at OEMs: Collaboration instead of “Clash of Clans” at Stellantis

21. October 2021 Having 14 car brands under one roof also means leveraging synergies. Questions for the head of software, hardware and AI development at Stellantis Joachim Langenwalter.

Software standards: A must for the automotive industry?

21. October 2021 "VW's Cariad software unit aims to disempower Bosch, Conti and ZF". "BMW calls for joint German operating system". "The software still works like a flea circus". Just a glance at some of the daily newspaper headlines of recent weeks shows: There is a need for discussion here. Our topic talk in cooperation with automotiveIT gets to the bottom of the matter.

CARLA: What the most used driving simulator is capable of

25. August 2021 The new CARLA simulation software can be used to run through scenarios and analyze traffic. Questions to the expert for 3-D object detection Walter Zimmer from the TU Munich.

Automotive industry: Artificial intelligence as a differentiating factor

18. August 2021 Michael Nolting's book "Artificial Intelligence in the Automotive Industry" looks at why artificial intelligence will become the competitive differentiator.

Plausibility checks of sensors: Particularly efficient in networks

22. June 2021 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.

How artificial intelligence recognizes objects and looks into the future

30. April 2021 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.

Many sensors, one digital twin: How does it work?

12. March 2021 In the coming months, the number of sensors in the Providentia++ project will more than triple. To fuse the data from cameras, radars, and lidars, scientists work with probabilities and evaluation pipelines. Questions for Leah Strand from the TU Munich.

Autonomous vehicles: Which sensors are used

14. October 2020 The sensors in your vehicle are only as good as circumstances allow. Complementing in-vehicle sensors with external information increases both precision and safety. An overview of sensors that are currently installed in vehicles, from cameras to lidar.

Sensors, perception, 5G: Which technologies are essential?

18. September 2020 Sensors, perception (with object recognition and tracking, as well as data fusion), and 5G radio technology are essential for Providentia++. These technologies play a key role in digitally representing traffic, recognizing vehicles, and transmitting data in real time.

How traffic data will enable new mobility services

13. September 2020 To warn of dangerous situations, avoid traffic jams, make autonomous vehicles more intelligent, and analyze traffic: These are just some of the reasons why we need traffic data. It lays the foundation for new intelligent services.

Providentia++: The four greatest challenges

3. September 2020 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. Here are the most important challenges ahead for Providentia++.