70 citations · 121 across the 29 of their papers we have counts for
30 papers
Open-Source Tool Based Framework for Automated Performance Evaluation of an AD Function
Daniel Becker, Sanath Konthala, Lutz Eckstein
As automation in the field of automated driving (AD) progresses, ensuring the safety and functionality of AD functions (ADFs) becomes crucial. Virtual scenario-based testing has em…
3D Point Cloud Compression with Recurrent Neural Network and Image Compression Methods
Till Beemelmanns, Yuchen Tao, Bastian Lampe +4
Storing and transmitting LiDAR point cloud data is essential for many AV applications, such as training data collection, remote control, cloud services or SLAM. However, due to the…
RobotKube: Orchestrating Large-Scale Cooperative Multi-Robot Systems with Kubernetes and ROS
Bastian Lampe, Lennart Reiher, Lukas Zanger +3
Modern cyber-physical systems (CPS) such as Cooperative Intelligent Transport Systems (C-ITS) are increasingly defined by the software which operates these systems. In practice, mi…
Simulative Performance Analysis of an AD Function with Road Network Variation
Daniel Becker, Guido Küppers, Lutz Eckstein
Automated driving functions (ADFs) have become increasingly popular in recent years. However, their safety must be assured. Thus, the verification and validation of these functions…
Economic Analysis of Smart Roadside Infrastructure Sensors for Connected and Automated Mobility
Laurent Kloeker, Gregor Joeken, Lutz Eckstein
Smart roadside infrastructure sensors in the form of intelligent transportation system stations (ITS-Ss) are increasingly deployed worldwide at relevant traffic nodes. The resultin…
Acquire Driving Scenarios Efficiently: A Framework for Prospective Assessment of Cost-Optimal Scenario Acquisition
Christoph Glasmacher, Michael Schuldes, Hendrik Weber +2
Scenario-based testing is becoming increasingly important in safety assurance for automated driving. However, comprehensive and sufficiently complete coverage of the scenario space…
Framework for Quality Evaluation of Smart Roadside Infrastructure Sensors for Automated Driving Applications
Laurent Kloeker, Chenghua Liu, Chao Wei +1
The use of smart roadside infrastructure sensors is highly relevant for future applications of connected and automated vehicles. External sensor technology in the form of intellige…
Combined Registration and Fusion of Evidential Occupancy Grid Maps for Live Digital Twins of Traffic
Raphael van Kempen, Laurenz Adrian Heidrich, Bastian Lampe +2
Cooperation of automated vehicles (AVs) can improve safety, efficiency and comfort in traffic. Digital twins of Cooperative Intelligent Transport Systems (C-ITS) play an important…
Data-Driven Occupancy Grid Mapping using Synthetic and Real-World Data
Raphael van Kempen, Bastian Lampe, Lennart Reiher +3
In perception tasks of automated vehicles (AVs) data-driven have often outperformed conventional approaches. This motivated us to develop a data-driven methodology to compute occup…
Road Network Variation Based on HD Map Analysis for the Simulative Safety Assurance of Automated Vehicles
Daniel Becker, Christian Geller, Lutz Eckstein
The validation and verification of automated driving functions (ADFs) is a challenging task on the journey of making those functions available to the public beyond the current rese…
Enabling Connectivity for Automated Mobility: A Novel MQTT-based Interface Evaluated in a 5G Case Study on Edge-Cloud Lidar Object Detection
Lennart Reiher, Bastian Lampe, Timo Woopen +3
Enabling secure and reliable high-bandwidth lowlatency connectivity between automated vehicles and external servers, intelligent infrastructure, and other road users is a central s…
Robust Environment Perception for Automated Driving: A Unified Learning Pipeline for Visual-Infrared Object Detection
Mohsen Vadidar, Ali Kariminezhad, Christian Mayr +2
The RGB complementary metal-oxidesemiconductor (CMOS) sensor works within the visible light spectrum. Therefore it is very sensitive to environmental light conditions. On the contr…
EMMI: Empathic Human-Machine Interaction for Establishing Trust in Automated Driving
Tobias Oetermann, Pia Dautzenberg, Gudrun Voß +10
Highly automated vehicles represent one of the most crucial development efforts in the automotive industry. In addition to the use of research vehicles, production vehicles for the…
An Automated Analysis Framework for Trajectory Datasets
Christoph Glasmacher, Robert Krajewski, Lutz Eckstein
Trajectory datasets of road users have become more important in the last years for safety validation of highly automated vehicles. Several naturalistic trajectory datasets with eac…
Corridor for new mobility Aachen-Düsseldorf: Methods and concepts of the research project ACCorD
Laurent Kloeker, Amarin Kloeker, Fabian Thomsen +11
With the Corridor for New Mobility Aachen - Düsseldorf, an integrated development environment is created, incorporating existing test capabilities, to systematically test and valid…
Highly accurate digital traffic recording as a basis for future mobility research: Methods and concepts of the research project HDV-Mess
Laurent Kloeker, Fabian Thomsen, Lutz Eckstein +6
The research project HDV-Mess aims at a currently missing, but very crucial component for addressing important challenges in the field of connected and automated driving on public…
Systematic Categorization of Influencing Factors on Radar-Based Perception to Facilitate Complex Real-World Data Evaluation
Maike Scholtes, Lutz Eckstein
For the assessment of machine perception for automated driving it is important to understand the influence of certain environment factors on the sensors used. Especially when inves…
A Review of Testing Object-Based Environment Perception for Safe Automated Driving
Michael Hoss, Maike Scholtes, Lutz Eckstein
Safety assurance of automated driving systems must consider uncertain environment perception. This paper reviews literature addressing how perception testing is realized as part of…
A Simulation-based End-to-End Learning Framework for Evidential Occupancy Grid Mapping
Raphael van Kempen, Bastian Lampe, Timo Woopen +1
Evidential occupancy grid maps (OGMs) are a popular representation of the environment of automated vehicles. Inverse sensor models (ISMs) are used to compute OGMs from sensor data…
Deep Inverse Sensor Models as Priors for evidential Occupancy Mapping
Daniel Bauer, Lars Kuhnert, Lutz Eckstein
With the recent boost in autonomous driving, increased attention has been paid on radars as an input for occupancy mapping. Besides their many benefits, the inference of occupied s…
6-Layer Model for a Structured Description and Categorization of Urban Traffic and Environment
Maike Scholtes, Lukas Westhofen, Lara Ruth Turner +11
Verification and validation of automated driving functions impose large challenges. Currently, scenario-based approaches are investigated in research and industry, aiming at a redu…
Real-Time Point Cloud Fusion of Multi-LiDAR Infrastructure Sensor Setups with Unknown Spatial Location and Orientation
Laurent Kloeker, Christian Kotulla, Lutz Eckstein
The use of infrastructure sensor technology for traffic detection has already been proven several times. However, extrinsic sensor calibration is still a challenge for the operator…
High-Precision Digital Traffic Recording with Multi-LiDAR Infrastructure Sensor Setups
Laurent Kloeker, Christian Geller, Amarin Kloeker +1
Large driving datasets are a key component in the current development and safeguarding of automated driving functions. Various methods can be used to collect such driving data reco…
Generation of Complex Road Networks Using a Simplified Logical Description for the Validation of Automated Vehicles
Daniel Becker, Fabian Ruß, Christian Geller +1
Simulation is a valuable building block for the verification and validation of automated driving functions (ADF). When simulating urban driving scenarios, simulation maps are one i…