27 citations · 35 across the 6 of their papers we have counts for
10 papers
Self-Assessment for Single-Object Tracking in Clutter Using Subjective Logic
Thomas Griebel, Johannes Müller, Paul Geisler +4
Reliable tracking algorithms are essential for automated driving. However, the existing consistency measures are not sufficient to meet the increasing safety demands in the automot…
Situation-Aware Environment Perception Using a Multi-Layer Attention Map
Matti Henning, Johannes Müller, Fabian Gies +2
Within the field of automated driving, a clear trend in environment perception tends towards more sensors, higher redundancy, and overall increase in computational power. This is m…
Motion Planning for Connected Automated Vehicles at Occluded Intersections With Infrastructure Sensors
Johannes Müller, Jan Strohbeck, Martin Herrmann +1
Motion planning at urban intersections that accounts for the situation context, handles occlusions, and deals with measurement and prediction uncertainty is a major challenge on th…
LMB Filter Based Tracking Allowing for Multiple Hypotheses in Object Reference Point Association*
Martin Herrmann, Aldi Piroli, Jan Strohbeck +2
Autonomous vehicles need precise knowledge on dynamic objects in their surroundings. Especially in urban areas with many objects and possible occlusions, an infrastructure system b…
Kalman Filter Meets Subjective Logic: A Self-Assessing Kalman Filter Using Subjective Logic
Thomas Griebel, Johannes Müller, Michael Buchholz +1
Self-assessment is a key to safety and robustness in automated driving. In order to design safer and more robust automated driving functions, the goal is to self-assess the perform…
LACI: Low-effort Automatic Calibration of Infrastructure Sensors
Johannes Müller, Martin Herrmann, Jan Strohbeck +2
Sensor calibration usually is a time consuming yet important task. While classical approaches are sensor-specific and often need calibration targets as well as a widely overlapping…
A Risk and Comfort Optimizing Motion Planning Scheme for Merging Scenarios
Johannes Müller, Michael Buchholz
Motion planning for merging scenarios accounting for measurement and prediction uncertainties is a major challenge on the way to autonomous driving. Classical methods subdivide the…
Environment Modeling Based on Generic Infrastructure Sensor Interfaces Using a Centralized Labeled-Multi-Bernoulli Filter
Martin Herrmann, Johannes Müller, Jan Strohbeck +1
Urban intersections put high demands on fully automated vehicles, in particular, if occlusion occurs. In order to resolve such and support vehicles in unclear situations, a popular…
A Trust Management and Misbehaviour Detection Mechanism for Multi-Agent Systems and its Application to Intelligent Transportation Systems
Johannes Müller, Tobias Meuser, Ralf Steinmetz +1
Cooperative information shared among a multi-agent system (MAS) can be useful to agents to efficiently fulfill their missions. Relying on wrong information, however, can have sever…
A Subjective-Logic-based Reliability Estimation Mechanism for Cooperative Information with Application to IV's Safety
Johannes Müller, Michael Gabb, Michael Buchholz
Use of cooperative information, distributed by road-side units, offers large potential for intelligent vehicles (IVs). As vehicle automation progresses and cooperative perception i…