The New BMW iDrive - Applied Processes and Methods to Assure High Usability. - Bernhard Niedermaier; Stephan Durach; Lutz Eckstein; Andreas Keinath (HCI (11), 2009)

Modular approach to energy efficient driver assistance incorporating driver acceptance. - Philipp Themann; Lutz Eckstein (Intelligent Vehicles Symposium, 2012)

Effects of ACC and FCW on Speed, Fuel Consumption, and Driving Safety. - Mohamed Benmimoun; Andreas Pütz; Adrian Zlocki; Lutz Eckstein (VTC Fall, 2012)

Optimal vehicle dynamics control for combined longitudinal and lateral autonomous vehicle guidance. - Alexander Katriniok; Jan P. Maschuw; Frederic Christen; Lutz Eckstein; Dirk Abel (ECC, 2013)

Sensitivity analysis for model based fusion of camera systems with navigation data. - Marc Wimmershoff; Christoph Klas; Adrian Zlocki; Lutz Eckstein (Intelligent Vehicles Symposium, 2013)

Integration of micro-CHP units into BEVs - Influence on the overall efficiency, emissions and the electric driving range. - Sidney Baltzer; Jorg Gissing; Peter Jeck; Thomas Lichius; Lutz Eckstein (Intelligent Vehicles Symposium, 2014)

Improving and simplifying the generation of reference trajectories by usage of road-aligned coordinate systems. - Janek Hudecek; Lutz Eckstein (Intelligent Vehicles Symposium, 2014)

Discrete dynamic optimization in automated driving systems to improve energy efficiency in cooperative networks. - Philipp Themann; Robert Krajewski; Lutz Eckstein (Intelligent Vehicles Symposium, 2014)

Definition of an embedded driver model for driving behavior prediction within the DESERVE platform. - Jens Klimke; Philipp Themann; Christoph Klas; Lutz Eckstein (ICSAMOS, 2014)

Impact of positioning uncertainty of vulnerable road users on risk minimization in collision avoidance systems. - Philipp Themann; Jens Kotte; Dominik Raudszus; Lutz Eckstein (Intelligent Vehicles Symposium, 2015)

A scenario-based assessment approach for automated driving by using time series classification of human-driving behaviour. - Christian Roesener; Felix Fahrenkrog; Axel Uhlig; Lutz Eckstein (ITSC, 2016)

Decoupled cooperative trajectory optimization for connected highly automated vehicles at urban intersections. - Robert Krajewski; Philipp Themann; Lutz Eckstein (Intelligent Vehicles Symposium, 2016)

Optimal Control of Series Plug-In Hybrid Electric Vehicles Considering the Cabin Heat Demand. - Jorg Gissing; Philipp Themann; Sidney Baltzer; Thomas Lichius; Lutz Eckstein (IEEE Trans. Control. Syst. Technol., 2016)

How safe is automated driving? Human driver models for safety performance assessment. - Christian Roesener; Johannes Hiller; Hendrik Weber; Lutz Eckstein (ITSC, 2017)

Privacy and initial information in automated driving - Evaluation of information demands and data sharing concerns. - Johanna Josten; Teresa Schmidt; Ralf Philipsen; Lutz Eckstein; Martina Ziefle (Intelligent Vehicles Symposium, 2017)

A-priori map information and path planning for automated valet-parking. - Sebastian Klaudt; Adrian Zlocki; Lutz Eckstein (Intelligent Vehicles Symposium, 2017)

The highD Dataset: A Drone Dataset of Naturalistic Vehicle Trajectories on German Highways for Validation of Highly Automated Driving Systems. - Robert Krajewski; Julian Bock; Laurent Kloeker; Lutz Eckstein (ITSC, 2018)

Data-Driven Maneuver Modeling using Generative Adversarial Networks and Variational Autoencoders for Safety Validation of Highly Automated Vehicles. - Robert Krajewski; Tobias Moers; Dominik Nerger; Lutz Eckstein (ITSC, 2018)

Modelling Human Driver Performance for Safety Assessment of Road Vehicle Automation. - Christian Roesener; Michael Harth; Hendrik Weber; Johanna Josten; Lutz Eckstein (ITSC, 2018)

Trajectory optimization for Car-Like Vehicles in Structured and Semi-Structured Environments. - Clemens Nietzschmann; Sebastian Klaudt; Christoph Klas; Devid Will; Lutz Eckstein (Intelligent Vehicles Symposium, 2018)

Kooperativ interagierende Automobile. - Christoph Stiller; Wolfram Burgard; Barbara Deml; Lutz Eckstein; Frank Flemisch (Autom., 2018)

A Novel Method for Designing Metaphor-Based Driver-Vehicle Interaction Concepts in Automated Vehicles. - Jan Bavendiek; Emily Oliveira; Lutz Eckstein (AHFE (13), 2019)

Fail-Operational Steer-By-Wire System for Autonomous Vehicles. - Minglu Li; Lutz Eckstein (ICVES, 2019)

Recognition and Pseudonymization of Data Privacy Relevant Areas in Videos for Compliance with GDPR. - Johannes Hiller; Michael Schuldes; Lutz Eckstein (ITSC, 2019)

A Dynamic Service-Oriented Software Architecture for Highly Automated Vehicles. - Alexandru Kampmann; Bassam Alrifaee; Markus Kohout; Andreas Wüstenberg; Timo Woopen; Marcus Nolte; Lutz Eckstein; Stefan Kowalewski (ITSC, 2019)

BézierVAE: Improved Trajectory Modeling using Variational Autoencoders for the Safety Validation of Highly Automated Vehicles. - Robert Krajewski; Tobias Moers; Adrian Meister; Lutz Eckstein (ITSC, 2019)

Deep, spatially coherent Inverse Sensor Models with Uncertainty Incorporation using the evidential Framework. - Daniel Bauer; Lars Kuhnert; Lutz Eckstein (IV, 2019)

Continuously Improving Model of Road User Movement Patterns using Recurrent Neural Networks at Intersections with Connected Sensors. - Julian Bock; Philipp Nolte; Lutz Eckstein (VEHITS, 2019)

VeGAN: Using GANs for Augmentation in Latent Space to Improve the Semantic Segmentation of Vehicles in Images From an Aerial Perspective. - Robert Krajewski; Tobias Moers; Lutz Eckstein (WACV, 2019)

Deep, spatially coherent Occupancy Maps based on Radar Measurements. - Daniel Bauer; Lars Kuhnert; Lutz Eckstein (CoRR, 2019)

Agile Requirement Engineering for a Cloud System for Automated and Networked Vehicles. - Armin Mokhtarian; Alexandru Kampmann; Bassam Alrifaee; Stefan Kowalewski; Bastian Lampe; Lutz Eckstein (ASD@DATE, 2020)

Evaluating HMI-Development Approaches from an Automotive Perspective. - Jan Bavendiek; Yannick Ostad; Lutz Eckstein (HCI (32), 2020)

Deep Inverse Sensor Models as Priors for evidential Occupancy Mapping. - Daniel Bauer; Lars Kuhnert; Lutz Eckstein (IROS, 2020)

Generation of Complex Road Networks Using a Simplified Logical Description for the Validation of Automated Vehicles. - Daniel Becker 007; Fabian Ruß; Christian Geller; Lutz Eckstein (ITSC, 2020)

High-Precision Digital Traffic Recording with Multi-LiDAR Infrastructure Sensor Setups*. - Laurent Kloeker; Christian Geller; Amarin Kloeker; Lutz Eckstein (ITSC, 2020)

Real-Time Point Cloud Fusion of Multi-LiDAR Infrastructure Sensor Setups with Unknown Spatial Location and Orientation. - Laurent Kloeker; Christian Kotulla; Lutz Eckstein (ITSC, 2020)

The rounD Dataset: A Drone Dataset of Road User Trajectories at Roundabouts in Germany. - Robert Krajewski; Tobias Moers; Julian Bock; Lennart Vater; Lutz Eckstein (ITSC, 2020)

A Sim2Real Deep Learning Approach for the Transformation of Images from Multiple Vehicle-Mounted Cameras to a Semantically Segmented Image in Bird's Eye View. - Lennart Reiher; Bastian Lampe; Lutz Eckstein (ITSC, 2020)

The inD Dataset: A Drone Dataset of Naturalistic Road User Trajectories at German Intersections. - Julian Bock; Robert Krajewski; Tobias Moers; Steffen Runde; Lennart Vater; Lutz Eckstein (IV, 2020)

Using Drones as Reference Sensors for Neural-Networks-Based Modeling of Automotive Perception Errors**The research leading to these results is funded by the Federal Ministry for Economic Affairs and Energy within the project "VVM - Verification and Validation Methods for Automated Vehicles Level 4 and 5". The authors would like to thank the consortium for the successful cooperation. - Robert Krajewski; Michael Hoss; Adrian Meister; Fabian Thomsen; Julian Bock; Lutz Eckstein (IV, 2020)

Reducing Uncertainty by Fusing Dynamic Occupancy Grid Maps in a Cloud-based Collective Environment Model. - Bastian Lampe; Raphael van Kempen; Timo Woopen; Alexandru Kampmann; Bassam Alrifaee; Lutz Eckstein (IV, 2020)

High-Precision Digital Traffic Recording with Multi-LiDAR Infrastructure Sensor Setups. - Laurent Kloeker; Christian Geller; Amarin Kloeker; Lutz Eckstein (CoRR, 2020)

An Expert Informed Approach to Assess Challenges in Automotive HMI Development and Their Implications on Development Processes. - Jan Bavendiek; Teresa Koch; Christopher Brockmeier; Lutz Eckstein (AHFE (12), 2021)

Investigating Kinematic Parameters of a Turning Seat as a Haptic and Kinesthetic HMI to Support the Take-Over Request in Automated Driving. - Steffen Jochum; Lotte Saupp; Jan Bavendiek; Christopher Brockmeier; Lutz Eckstein (AHFE (12), 2021)

Utilization and Potentials of Unmanned Aerial Vehicles (UAVs) in the Field of Automated Driving: A Survey. - Laurent Kloeker; Tobias Moers; Lennart Vater; Adrian Zlocki; Lutz Eckstein (ICVISP, 2021)

Drone-based Generation of Sensor Reference and Training Data for Highly Automated Vehicles. - Robert Krajewski; Lennart Vater; Marvin Klimke; Tobias Moers; Julian Bock; Lutz Eckstein (ITSC, 2021)

Aggregation of Road Characteristics from Online Maps and Evaluation of Datasets. - Johannes Hiller; Fabian Müller; Lutz Eckstein (IV, 2021)

A Simulation-based End-to-End Learning Framework for Evidential Occupancy Grid Mapping. - Raphael van Kempen; Bastian Lampe; Timo Woopen; Lutz Eckstein (IV, 2021)

Comparison of Camera-Equipped Drones and Infrastructure Sensors for Creating Trajectory Datasets of Road Users. - Amarin Kloeker; Robert Krajewski; Lutz Eckstein (VEHITS, 2021)

6-Layer Model for a Structured Description and Categorization of Urban Traffic and Environment. - Maike Scholtes; Lukas Westhofen 001; Lara Ruth Turner; Katrin Lotto; Michael Schuldes; Hendrik Weber; Nicolas Wagener; Christian Neurohr; Martin Bollmann; Franziska Körtke; Johannes Hiller; Michael Hoss; et al. (IEEE Access, 2021)

A data-driven approach towards the full anthropometric measurements prediction via Generalized Regression Neural Networks. - Lining Wang; Tien Ju Lee; Jan Bavendiek; Lutz Eckstein (Appl. Soft Comput., 2021)

A Review of Testing Object-Based Environment Perception for Safe Automated Driving. - Michael Hoss; Maike Scholtes; Lutz Eckstein (CoRR, 2021)

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; Philip Trettner; Tim Elsner; Julius Nehring-Wirxel; Kersten Schuster; Leif Kobbelt; Michael Hoesch (CoRR, 2021)

Corridor for new mobility Aachen-Düsseldorf: Methods and concepts of the research project ACCorD. - Laurent Kloeker; Amarin Kloeker; Fabian Thomsen; Armin Erraji; Lutz Eckstein; Serge Lamberty; Adrian Fazekas; Eszter Kalló; Markus Oeser; Charlotte Fléchon; Jochen Lohmiller; Pascal Pfeiffer; et al. (CoRR, 2021)

Generic Approach to Optimized Placement of Smart Roadside Infrastructure Sensors Using 3D Digital Maps. - Laurent Kloeker; Julian Quakernack; Bastian Lampe; Lutz Eckstein (ITSC, 2022)

3D Point Cloud Compression with Recurrent Neural Network and Image Compression Methods. - Till Beemelmanns; Yuchen Tao; Bastian Lampe; Lennart Reiher; Raphael van Kempen; Timo Woopen; Lutz Eckstein (IV, 2022)

The exiD Dataset: A Real-World Trajectory Dataset of Highly Interactive Highway Scenarios in Germany. - Tobias Moers; Lennart Vater; Robert Krajewski; Julian Bock; Adrian Zlocki; Lutz Eckstein (IV, 2022)

Robust Environment Perception for Automated Driving: A Unified Learning Pipeline for Visual-Infrared Object Detection. - Mohsen Vadidar; Ali Kariminezhad; Christian Mayr 003; Laurent Kloeker; Lutz Eckstein (IV, 2022)

An Automated Analysis Framework for Trajectory Datasets. - Christoph Glasmacher; Robert Krajewski; Lutz Eckstein (CoRR, 2022)

EMMI: Empathic Human-Machine Interaction for Establishing Trust in Automated Driving. - Tobias Oetermann; Pia S. C. Dautzenberg; Gudrun Mechthild Irmgard Voß; Christopher Brockmeier; Stefan Ladwig; Patrick Gebhard; Tanja Schneeberger; Markus Funk; Raymond Brueckner; Felix Schäfer; Norbert Helff; Andreas Gomer; et al. (CoRR, 2022)

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; Raphael van Kempen; Till Beemelmanns; Lutz Eckstein (CoRR, 2022)

Road Network Variation Based on HD Map Analysis for the Simulative Safety Assurance of Automated Vehicles. - Daniel Becker 007; Christian Geller; Lutz Eckstein (CoRR, 2022)

Data-Driven Occupancy Grid Mapping using Synthetic and Real-World Data. - Raphael van Kempen; Bastian Lampe; Lennart Reiher; Timo Woopen; Till Beemelmanns; Lutz Eckstein (CoRR, 2022)

Enhancing Lidar-Based Object Detection in Adverse Weather Using Offset Sequences in Time. - Raphael van Kempen; Tim Rehbronn; Abin Jose; Johannes Stegmaier; Bastian Lampe; Timo Woopen; Lutz Eckstein (ICECET, 2023)

Sim-to-Real Domain Adaptation of Infrastructure Sensor Lidar Point Clouds using Generative Adversarial Networks. - Amarin Kloeker; Yangyi Liu; Mischa Maier; Lutz Eckstein (ICECET, 2023)

Open-Source Tool Based Framework for Automated Performance Evaluation of an AD Function. - Sanath Konthala; Daniel Becker 007; Lutz Eckstein (ICECET, 2023)

Scalable Real-Time Multi Object Tracking for Automated Driving Using Intelligent Infrastructure. - Fabian Thomsen; Maximilian Ortmann; Lutz Eckstein (ICECET, 2023)

Acquire Driving Scenarios Efficiently: A Framework for Prospective Assessment of Cost-Optimal Scenario Acquisition. - Christoph Glasmacher; Michael Schuldes; Hendrik Weber; Nicolas Wagener; Lutz Eckstein (ITSC, 2023)

Economic Analysis of Smart Roadside Infrastructure Sensors for Connected and Automated Mobility. - Laurent Kloeker; Gregor Joeken; Lutz Eckstein (ITSC, 2023)

RobotKube: Orchestrating Large-Scale Cooperative Multi-Robot Systems with Kubernetes and ROS. - Bastian Lampe; Lennart Reiher; Lukas Zanger; Timo Woopen; Raphael van Kempen; Lutz Eckstein (ITSC, 2023)

Combined Registration and Fusion of Evidential Occupancy Grid Maps for Live Digital Twins of Traffic. - Raphael van Kempen; Laurenz Adrian Heidrich; Bastian Lampe; Timo Woopen; Lutz Eckstein (IV, 2023)

Framework for Quality Evaluation of Smart Roadside Infrastructure Sensors for Automated Driving Applications. - Laurent Kloeker; Chenghua Liu; Chao Wei; Lutz Eckstein (IV, 2023)

FPGA-based Acceleration of Lidar Point Cloud Processing and Detection on the Edge. - Cecilia Latotzke; Amarin Kloeker; Simon Schoening; Fabian Kemper 002; Mazen Slimi; Lutz Eckstein; Tobias Gemmeke (IV, 2023)

Holistic Driving Scenario Concept for Urban Traffic. - Hendrik Weber; Christoph Glasmacher; Michael Schuldes; Nicolas Wagener; Lutz Eckstein (IV, 2023)

Generation of Concrete Parameters from Logical Urban Driving Scenarios Based on Hybrid Graphs. - Christoph Glasmacher; Hendrik Weber; Michael Schuldes; Nicolas Wagener; Lutz Eckstein (VEHITS, 2023)

Simulative Performance Analysis of an AD Function with Road Network Variation. - Daniel Becker 007; Guido Küppers; Lutz Eckstein (CoRR, 2023)

Explainable Multi-Camera 3D Object Detection with Transformer-Based Saliency Maps. - Till Beemelmanns; Wassim Zahr; Lutz Eckstein (CoRR, 2023)

Enabling the Deployment of Any-Scale Robotic Applications in Microservice Architectures through Automated Containerization. - Jean-Pierre Busch; Lennart Reiher; Lutz Eckstein (ICRA, 2024)

V2AIX: A Multi-Modal Real-World Dataset of ETSI ITS V2X Messages in Public Road Traffic. - Guido Küppers; Jean-Pierre Busch; Lennart Reiher; Lutz Eckstein (ITSC, 2024)

Scenario-Based Thermal Management Parametrization Through Deep Reinforcement Learning. - Thomas Rudolf; Philip Muhl; Sören Hohmann; Lutz Eckstein (ITSC, 2024)

MultiCorrupt: A Multi-Modal Robustness Dataset and Benchmark of LiDAR-Camera Fusion for 3D Object Detection. - Till Beemelmanns; Quan Zhang; Christian Geller; Lutz Eckstein (IV, 2024)

CARLOS: An Open, Modular, and Scalable Simulation Framework for the Development and Testing of Software for C-ITS. - Christian Geller; Benedikt Haas; Amarin Kloeker; Jona Hermens; Bastian Lampe; Till Beemelmanns; Lutz Eckstein (IV, 2024)

Causality-based Transfer of Driving Scenarios to Unseen Intersections. - Christoph Glasmacher; Michael Schuldes; Sleiman El Masri; Lutz Eckstein (IV, 2024)

Towards a Completeness Argumentation for Scenario Concepts. - Christoph Glasmacher; Hendrik Weber; Michael Schuldes; Lutz Eckstein (IV, 2024)

scenario.center: Methods from Real-world Data to a Scenario Database. - Michael Schuldes; Christoph Glasmacher; Lutz Eckstein (IV, 2024)

Determining the Tactical Challenge of Scenarios to Efficiently Test Automated Driving Systems. - Lennart Vater; Sven Tarlowski; Michael Schuldes; Lutz Eckstein (IV, 2024)

Detecting Edge Cases from Trajectory Datasets Using Deep Learning Based Outlier Detection. - Marcel Sonntag; Lennart Vater; Roman Vuskov; Lutz Eckstein (VEHITS, 2024)

MultiCorrupt: A Multi-Modal Robustness Dataset and Benchmark of LiDAR-Camera Fusion for 3D Object Detection. - Till Beemelmanns; Quan Zhang; Lutz Eckstein (CoRR, 2024)

Towards a Completeness Argumentation for Scenario Concepts. - Christoph Glasmacher; Hendrik Weber; Lutz Eckstein (CoRR, 2024)

Comparison of Parametrization Approaches for Scenario-Based Testing. - Christoph Glasmacher; Marcel Sonntag; Lutz Eckstein (VEHITS, 2025)

OCCUQ: Exploring Efficient Uncertainty Quantification for 3D Occupancy Prediction. - Severin Heidrich; Till Beemelmanns; Alexey Nekrasov 001; Bastian Leibe; Lutz Eckstein (CoRR, 2025)