218 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Universität UlmDE13 papers
- Esslingen University of Applied SciencesDE5 papers
- Leiden UniversityNL5 papers
- Karlsruhe Institute of TechnologyDE4 papers
- Saarland UniversityDE4 papers
- University of StuttgartDE4 papers
- University of TübingenDE4 papers
- Forschungszentrum JülichDE3 papers
- RheinMain University of Applied SciencesDE3 papers
- University of Applied Sciences LeidenNL3 papers
- University of GöttingenDE3 papers
- University of SiegenDE3 papers
11 papers · 1 filter
Active Output Selection Strategies for Multiple Learning Regression Models
Adrian Prochaska, Julien Pillas, Bernard Bäker
Active learning shows promise to decrease test bench time for model-based drivability calibration. This paper presents a new strategy for active output selection, which suits the n…
Robust Model Predictive Longitudinal Position Tracking Control for an Autonomous Vehicle Based on Multiple Models
André Kempf, Markus Herrmann-Wicklmayr, Steffen Müller
The aim of this work is to control the longitudinal position of an autonomous vehicle with an internal combustion engine. The powertrain has an inherent dead-time characteristic an…
A Fleet Learning Architecture for Enhanced Behavior Predictions during Challenging External Conditions
Florian Wirthmüller, Marvin Klimke, Julian Schlechtriemen +2
Already today, driver assistance systems help to make daily traffic more comfortable and safer. However, there are still situations that are quite rare but are hard to handle at th…
Holistic Grid Fusion Based Stop Line Estimation
Runsheng Xu, Faezeh Tafazzoli, Li Zhang +3
Intersection scenarios provide the most complex traffic situations in Autonomous Driving and Driving Assistance Systems. Knowing where to stop in advance in an intersection is an e…
Driver Assistance for Safe and Comfortable On-Ramp Merging Using Environment Models Extended through V2X Communication and Role-Based Behavior Predictions
Lucas Eiermann, Florian Wirthmüller, Kay Massow +2
Modern driver assistance systems as well as autonomous vehicles take their decisions based on local maps of the environment. These maps include, for example, surrounding moving obj…
Using Machine Learning to Detect Ghost Images in Automotive Radar
Florian Kraus, Nicolas Scheiner, Werner Ritter +1
Radar sensors are an important part of driver assistance systems and intelligent vehicles due to their robustness against all kinds of adverse conditions, e.g., fog, snow, rain, or…
Towards Incorporating Contextual Knowledge into the Prediction of Driving Behavior
Florian Wirthmüller, Julian Schlechtriemen, Jochen Hipp +1
Predicting the behavior of surrounding traffic participants is crucial for advanced driver assistance systems and autonomous driving. Most researchers however do not consider conte…
Off-the-shelf sensor vs. experimental radar -- How much resolution is necessary in automotive radar classification?
Nicolas Scheiner, Ole Schumann, Florian Kraus +3
Radar-based road user detection is an important topic in the context of autonomous driving applications. The resolution of conventional automotive radar sensors results in a sparse…
Estimating End-to-End Latencies in Automotive Cyber-physical Systems
Max J. Friese, Dirk Nowotka
Controller networks in today's automotive systems consist of more than 100 ECUs connected by various bus protocols. Seamless operation of the entire system requires a well-orchestr…
Scan-based Semantic Segmentation of LiDAR Point Clouds: An Experimental Study
Larissa T. Triess, David Peter, Christoph B. Rist +1
Autonomous vehicles need to have a semantic understanding of the three-dimensional world around them in order to reason about their environment. State of the art methods use deep n…
Approximating the quantum approximate optimization algorithm with digital-analog interactions
David Headley, Thorge Müller, Ana Martin +3
The quantum approximate optimisation algorithm was proposed as a heuristic method for solving combinatorial optimisation problems on near-term quantum computers and may be among th…