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.
1. July 2022 Since the beginning of research on the digital twin, AI specialist Cognition Factory GmbH has focused on processing camera data. In the meantime Dr. Claus Lenz has deployed a large-scale platform
1. July 2022 Expand the test track, deploy new sensors, decentralize software architecture, fuse sensor data for 24/7 operation of a real-time digital twin, and make data packets public: TU Munich has decisively advanced the Providentia++ research project.
11. May 2022 Elektrobit lays the foundation for Big Data evaluations of traffic data. Simon Tiedemann on the developments in P++.
10. April 2022 Data fusion, perception, and prediction were the three topics fortiss addressed in the Providentia++ research project. Bernhard Blieninger takes stock.
30. March 2022 For Lutz Eckstein, "the" future concept for mobility does not exist, but rather a juxtaposition of many approaches. The professor from RWTH Aachen in conversation.
15. February 2022 Yunex uses the data from the A9 testfield to investigate Time to Collision in more detail. A field report.
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.
6. August 2021 Expanding the A9 test section for autonomous and connected driving required a great deal of research and pragmatic decision-making. Now that it has been accomplished and the scientists are at work, we look back at eight challenges and their solutions.
31. July 2021 To predict movements, many trajectory options must be taken into consideration and prioritized. The FloMo model works with probabilities and has been trained on the basis of three datasets. Its performance is improved by a proposed method of stabilizing training flows.
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.
12. April 2021 When highly automated vehicles are on the road, human drivers tend to adapt their behavior, driving more slowly and safely. New findings from traffic psychologist Vanessa Stange from the Technische Universität Braunschweig.
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.
26. February 2021 In Germany, level 4 autonomous vehicles will be allowed to drive on the roads from 2022, according to a draft bill from the Federal Ministry of Transport. Accident researcher Dr.-Ing. Matthias Kühn discusses autonomous driving and safety.
26. February 2021 High-resolution road maps are a prerequisite for automated and autonomous driving. They provide vehicles with the framework in which they can move. 3D Mapping Solutions is measuring the streets with millimeter precision and creating HD maps for Providentia++.
4. November 2020 Recognizing different vehicles digitally is a challenge in itself. Doing this in real time: even more so. Dr. Claus Lenz from Providentia++ partner Cognition Factory discusses meeting the challenge of identifying vehicles on the A9 highway.
28. October 2020 Providentia++-scientist Venkatnarayanan Lakshminarasimhan from the Technical University of Munich is researching how vehicles communicate with each other and with the infrastructure. His goal: to use network resources as efficiently as possible.
26. September 2020 To find out how accurate the measurements of the digital twin are, fortiss and the DLR dispatched a helicopter with an integrated camera system. This allowed them to determine the exact position of the vehicles on the highway.
27. August 2020 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.
20. August 2020 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.
13. August 2020 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.
1. May 2020 Since the start of the Providentia research project in 2017, various scientific papers have been published – many of them in English. An overview, including topics such as 5G-based intelligent infrastructure, pedestrian motion prediction, and moving network convoys.