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ORCIDLutz Eckstein
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- affiliation: RWTH Aachen University, Germany
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2020 – today
- 2024
[c65]Jean-Pierre Busch, Lennart Reiher, Lutz Eckstein:
Enabling the Deployment of Any-Scale Robotic Applications in Microservice Architectures through Automated Containerization. ICRA 2024: 17650-17656- [c64]Christoph Glasmacher, Hendrik Weber, Michael Schuldes, Lutz Eckstein:
Towards a Completeness Argumentation for Scenario Concepts. IV 2024: 1106-1111 - [c63]Michael Schuldes, Christoph Glasmacher, Lutz Eckstein:
scenario.center: Methods from Real-world Data to a Scenario Database. IV 2024: 1119-1126 - [c62]Lennart Vater, Sven Tarlowski, Michael Schuldes, Lutz Eckstein:
Determining the Tactical Challenge of Scenarios to Efficiently Test Automated Driving Systems. IV 2024: 1266-1271 - [c61]Christian Geller, Benedikt Haas, Amarin Kloeker, Jona Hermens, Bastian Lampe, Till Beemelmanns, Lutz Eckstein:
CARLOS: An Open, Modular, and Scalable Simulation Framework for the Development and Testing of Software for C-ITS. IV 2024: 3100-3106 - [c60]Christoph Glasmacher, Michael Schuldes, Sleiman El Masri, Lutz Eckstein:
Causality-based Transfer of Driving Scenarios to Unseen Intersections. IV 2024: 3134-3139 - [c59]Till Beemelmanns, Quan Zhang, Christian Geller, Lutz Eckstein:
MultiCorrupt: A Multi-Modal Robustness Dataset and Benchmark of LiDAR-Camera Fusion for 3D Object Detection. IV 2024: 3255-3261 - [c58]Marcel Sonntag, Lennart Vater, Roman Vuskov, Lutz Eckstein:
Detecting Edge Cases from Trajectory Datasets Using Deep Learning Based Outlier Detection. VEHITS 2024: 31-39 - [i39]Raphael van Kempen, Tim Rehbronn, Abin Jose, Johannes Stegmaier, Bastian Lampe
, Timo Woopen, Lutz Eckstein:
Enhancing Lidar-based Object Detection in Adverse Weather using Offset Sequences in Time. CoRR abs/2401.09049 (2024) - [i38]Till Beemelmanns, Quan Zhang, Lutz Eckstein:
MultiCorrupt: A Multi-Modal Robustness Dataset and Benchmark of LiDAR-Camera Fusion for 3D Object Detection. CoRR abs/2402.11677 (2024) - [i37]Till Beemelmanns, Yuchen Tao, Bastian Lampe, Lennart Reiher, Raphael van Kempen, Timo Woopen, Lutz Eckstein:
3D Point Cloud Compression with Recurrent Neural Network and Image Compression Methods. CoRR abs/2402.11680 (2024) - [i36]Guido Küppers, Jean-Pierre Busch, Lennart Reiher, Lutz Eckstein:
V2AIX: A Multi-Modal Real-World Dataset of ETSI ITS V2X Messages in Public Road Traffic. CoRR abs/2403.10221 (2024) - [i35]Christian Geller, Benedikt Haas, Amarin Kloeker, Jona Hermens, Bastian Lampe, Till Beemelmanns, Lutz Eckstein:
CARLOS: An Open, Modular, and Scalable Simulation Framework for the Development and Testing of Software for C-ITS. CoRR abs/2404.01836 (2024) - [i34]Christoph Glasmacher, Hendrik Weber, Lutz Eckstein:
Towards a Completeness Argumentation for Scenario Concepts. CoRR abs/2404.01934 (2024) - [i33]Christoph Glasmacher, Michael Schuldes, Sleiman El Masri, Lutz Eckstein:
Causality-based Transfer of Driving Scenarios to Unseen Intersections. CoRR abs/2404.02046 (2024) - [i32]Michael Schuldes, Christoph Glasmacher, Lutz Eckstein:
scenario.center: Methods from Real-world Data to a Scenario Database. CoRR abs/2404.02561 (2024) - [i31]Lennart Vater, Sven Tarlowski, Michael Schuldes, Lutz Eckstein:
Determining the Tactical Challenge of Scenarios to Efficiently Test Automated Driving Systems. CoRR abs/2404.02599 (2024) - [i30]Daniel Becker, Sanath Konthala, Lutz Eckstein:
Open-Source Tool Based Framework for Automated Performance Evaluation of an AD Function. CoRR abs/2406.16362 (2024) - [i29]Thomas Rudolf, Philip Muhl, Sören Hohmann, Lutz Eckstein:
Scenario-based Thermal Management Parametrization Through Deep Reinforcement Learning. CoRR abs/2408.02022 (2024) - 2023
- [c57]Christoph Glasmacher, Michael Schuldes, Hendrik Weber, Nicolas Wagener, Lutz Eckstein:
Acquire Driving Scenarios Efficiently: A Framework for Prospective Assessment of Cost-Optimal Scenario Acquisition. ITSC 2023: 1971-1976 - [c56]Laurent Kloeker, Gregor Joeken, Lutz Eckstein:
Economic Analysis of Smart Roadside Infrastructure Sensors for Connected and Automated Mobility. ITSC 2023: 2331-2336 - [c55]Bastian Lampe, Lennart Reiher, Lukas Zanger, Timo Woopen, Raphael van Kempen, Lutz Eckstein:
RobotKube: Orchestrating Large-Scale Cooperative Multi-Robot Systems with Kubernetes and ROS. ITSC 2023: 2719-2725 - [c54]Raphael van Kempen, Laurenz Adrian Heidrich, Bastian Lampe, Timo Woopen, Lutz Eckstein:
Combined Registration and Fusion of Evidential Occupancy Grid Maps for Live Digital Twins of Traffic. IV 2023: 1-6 - [c53]Laurent Kloeker, Chenghua Liu, Chao Wei, Lutz Eckstein:
Framework for Quality Evaluation of Smart Roadside Infrastructure Sensors for Automated Driving Applications. IV 2023: 1-7 - [c52]Cecilia Latotzke, Amarin Kloeker, Simon Schoening, Fabian Kemper, Mazen Slimi, Lutz Eckstein, Tobias Gemmeke:
FPGA-based Acceleration of Lidar Point Cloud Processing and Detection on the Edge. IV 2023: 1-8 - [c51]Hendrik Weber, Christoph Glasmacher, Michael Schuldes, Nicolas Wagener, Lutz Eckstein:
Holistic Driving Scenario Concept for Urban Traffic. IV 2023: 1-8 - [c50]Christoph Glasmacher, Hendrik Weber, Michael Schuldes, Nicolas Wagener, Lutz Eckstein:
Generation of Concrete Parameters from Logical Urban Driving Scenarios Based on Hybrid Graphs. VEHITS 2023: 215-222 - [i28]Raphael van Kempen, Laurenz Adrian Heidrich, Bastian Lampe, Timo Woopen, Lutz Eckstein:
Combined Registration and Fusion of Evidential Occupancy Grid Maps for Live Digital Twins of Traffic. CoRR abs/2304.03578 (2023) - [i27]Laurent Kloeker, Chenghua Liu, Chao Wei, Lutz Eckstein:
Framework for Quality Evaluation of Smart Roadside Infrastructure Sensors for Automated Driving Applications. CoRR abs/2304.07745 (2023) - [i26]Christoph Glasmacher, Michael Schuldes, Hendrik Weber, Nicolas Wagener, Lutz Eckstein:
Acquire Driving Scenarios Efficiently: A Framework for Prospective Assessment of Cost-Optimal Scenario Acquisition. CoRR abs/2307.11647 (2023) - [i25]Daniel Becker, Guido Küppers, Lutz Eckstein:
Simulative Performance Analysis of an AD Function with Road Network Variation. CoRR abs/2308.04446 (2023) - [i24]Bastian Lampe, Lennart Reiher, Lukas Zanger, Timo Woopen, Raphael van Kempen, Lutz Eckstein:
RobotKube: Orchestrating Large-Scale Cooperative Multi-Robot Systems with Kubernetes and ROS. CoRR abs/2308.07053 (2023) - [i23]Jean-Pierre Busch, Lennart Reiher, Lutz Eckstein:
Enabling the Deployment of Any-Scale Robotic Applications in Microservice Architectures through Automated Containerization. CoRR abs/2309.06611 (2023) - [i22]Till Beemelmanns, Wassim Zahr, Lutz Eckstein:
Explainable Multi-Camera 3D Object Detection with Transformer-Based Saliency Maps. CoRR abs/2312.14606 (2023) - 2022
- [c49]Laurent Kloeker, Julian Quakernack, Bastian Lampe, Lutz Eckstein:
Generic Approach to Optimized Placement of Smart Roadside Infrastructure Sensors Using 3D Digital Maps. ITSC 2022: 1311-1316 - [c48]Till Beemelmanns, Yuchen Tao, Bastian Lampe, Lennart Reiher, Raphael van Kempen, Timo Woopen, Lutz Eckstein:
3D Point Cloud Compression with Recurrent Neural Network and Image Compression Methods. IV 2022: 345-351 - [c47]Mohsen Vadidar, Ali Kariminezhad, Christian Mayr, Laurent Kloeker, Lutz Eckstein:
Robust Environment Perception for Automated Driving: A Unified Learning Pipeline for Visual-Infrared Object Detection. IV 2022: 367-374 - [c46]Tobias Moers, Lennart Vater, Robert Krajewski, Julian Bock, Adrian Zlocki, Lutz Eckstein:
The exiD Dataset: A Real-World Trajectory Dataset of Highly Interactive Highway Scenarios in Germany. IV 2022: 958-964 - [i21]Christoph Glasmacher, Robert Krajewski, Lutz Eckstein:
An Automated Analysis Framework for Trajectory Datasets. CoRR abs/2202.07438 (2022) - [i20]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, Lutz Eckstein:
EMMI: Empathic Human-Machine Interaction for Establishing Trust in Automated Driving. CoRR abs/2204.06377 (2022) - [i19]Mohsen Vadidar, Ali Kariminezhad, Christian Mayr, Laurent Kloeker, Lutz Eckstein:
Robust Environment Perception for Automated Driving: A Unified Learning Pipeline for Visual-Infrared Object Detection. CoRR abs/2206.03943 (2022) - [i18]Lennart Reiher, Bastian Lampe, Timo Woopen, Raphael van Kempen, Till Beemelmanns, Lutz Eckstein:
Enabling Connectivity for Automated Mobility: A Novel MQTT-based Interface Evaluated in a 5G Case Study on Edge-Cloud Lidar Object Detection. CoRR abs/2209.03630 (2022) - [i17]Daniel Becker, Christian Geller, Lutz Eckstein:
Road Network Variation Based on HD Map Analysis for the Simulative Safety Assurance of Automated Vehicles. CoRR abs/2210.00853 (2022) - [i16]Raphael van Kempen, Bastian Lampe, Lennart Reiher, Timo Woopen, Till Beemelmanns, Lutz Eckstein:
Data-Driven Occupancy Grid Mapping using Synthetic and Real-World Data. CoRR abs/2211.08278 (2022) - 2021
- [j4]Maike Scholtes, Lukas Westhofen, Lara Ruth Turner, Katrin Lotto, Michael Schuldes, Hendrik Weber, Nicolas Wagener, Christian Neurohr, Martin Bollmann, Franziska Körtke, Johannes Hiller, Michael Hoss, Julian Bock, Lutz Eckstein:
6-Layer Model for a Structured Description and Categorization of Urban Traffic and Environment. IEEE Access 9: 59131-59147 (2021) - [j3]Lining Wang, Tien Ju Lee, Jan Bavendiek, Lutz Eckstein:
A data-driven approach towards the full anthropometric measurements prediction via Generalized Regression Neural Networks. Appl. Soft Comput. 109: 107551 (2021) - [c45]Jan Bavendiek, Teresa Koch, Christopher Brockmeier, Lutz Eckstein:
An Expert Informed Approach to Assess Challenges in Automotive HMI Development and Their Implications on Development Processes. AHFE (12) 2021: 181-188 - [c44]Steffen Jochum, Lotte Saupp, Jan Bavendiek, Christopher Brockmeier, Lutz Eckstein:
Investigating Kinematic Parameters of a Turning Seat as a Haptic and Kinesthetic HMI to Support the Take-Over Request in Automated Driving. AHFE (12) 2021: 301-307 - [c43]Laurent Kloeker, Tobias Moers, Lennart Vater, Adrian Zlocki, Lutz Eckstein:
Utilization and Potentials of Unmanned Aerial Vehicles (UAVs) in the Field of Automated Driving: A Survey. ICVISP 2021: 9-17 - [c42]Robert Krajewski, Lennart Vater, Marvin Klimke, Tobias Moers, Julian Bock, Lutz Eckstein:
Drone-based Generation of Sensor Reference and Training Data for Highly Automated Vehicles. ITSC 2021: 3067-3074 - [c41]Johannes Hiller, Fabian Müller, Lutz Eckstein:
Aggregation of Road Characteristics from Online Maps and Evaluation of Datasets. IV 2021: 208-214 - [c40]Raphael van Kempen, Bastian Lampe, Timo Woopen, Lutz Eckstein:
A Simulation-based End-to-End Learning Framework for Evidential Occupancy Grid Mapping. IV 2021: 934-939 - [c39]Amarin Kloeker, Robert Krajewski, Lutz Eckstein:
Comparison of Camera-Equipped Drones and Infrastructure Sensors for Creating Trajectory Datasets of Road Users. VEHITS 2021: 161-170 - [i15]Michael Hoss, Maike Scholtes, Lutz Eckstein:
A Review of Testing Object-Based Environment Perception for Safe Automated Driving. CoRR abs/2102.08460 (2021) - [i14]Raphael van Kempen, Bastian Lampe, Timo Woopen, Lutz Eckstein:
A Simulation-based End-to-End Learning Framework for Evidential Occupancy Grid Mapping. CoRR abs/2102.12718 (2021) - [i13]Laurent Kloeker, Fabian Thomsen, Lutz Eckstein, Philip Trettner, Tim Elsner, Julius Nehring-Wirxel, Kersten Schuster, Leif Kobbelt, Michael Hoesch:
Highly accurate digital traffic recording as a basis for future mobility research: Methods and concepts of the research project HDV-Mess. CoRR abs/2106.04175 (2021) - [i12]Laurent Kloeker, Amarin Kloeker, Fabian Thomsen, Armin Erraji, Lutz Eckstein, Serge Lamberty, Adrian Fazekas, Eszter Kalló, Markus Oeser, Charlotte Fléchon, Jochen Lohmiller, Pascal Pfeiffer, Martin Sommer, Helen Winter:
Corridor for new mobility Aachen-Düsseldorf: Methods and concepts of the research project ACCorD. CoRR abs/2107.14048 (2021) - 2020
- [c38]Armin Mokhtarian, Alexandru Kampmann, Bassam Alrifaee, Stefan Kowalewski, Bastian Lampe, Lutz Eckstein:
Agile Requirement Engineering for a Cloud System for Automated and Networked Vehicles. ASD@DATE 2020: 4:1-4:8 - [c37]Jan Bavendiek, Yannick Ostad, Lutz Eckstein:
Evaluating HMI-Development Approaches from an Automotive Perspective. HCI (32) 2020: 199-216 - [c36]Daniel Bauer, Lars Kuhnert, Lutz Eckstein:
Deep Inverse Sensor Models as Priors for evidential Occupancy Mapping. IROS 2020: 6032-3067 - [c35]Daniel Becker, Fabian Ruß, Christian Geller, Lutz Eckstein:
Generation of Complex Road Networks Using a Simplified Logical Description for the Validation of Automated Vehicles. ITSC 2020: 1-7 - [c34]Laurent Kloeker, Christian Geller, Amarin Kloeker, Lutz Eckstein:
High-Precision Digital Traffic Recording with Multi-LiDAR Infrastructure Sensor Setups*. ITSC 2020: 1-8 - [c33]Laurent Kloeker, Christian Kotulla, Lutz Eckstein:
Real-Time Point Cloud Fusion of Multi-LiDAR Infrastructure Sensor Setups with Unknown Spatial Location and Orientation. ITSC 2020: 1-8 - [c32]Robert Krajewski, Tobias Moers, Julian Bock, Lennart Vater, Lutz Eckstein:
The rounD Dataset: A Drone Dataset of Road User Trajectories at Roundabouts in Germany. ITSC 2020: 1-6 - [c31]Lennart Reiher, Bastian Lampe, Lutz Eckstein:
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. ITSC 2020: 1-7 - [c30]Robert Krajewski, Michael Hoss, Adrian Meister, Fabian Thomsen, Julian Bock, Lutz Eckstein:
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. IV 2020: 708-715 - [c29]Bastian Lampe, Raphael van Kempen, Timo Woopen, Alexandru Kampmann, Bassam Alrifaee, Lutz Eckstein:
Reducing Uncertainty by Fusing Dynamic Occupancy Grid Maps in a Cloud-based Collective Environment Model. IV 2020: 837-843 - [c28]Julian Bock, Robert Krajewski, Tobias Moers, Steffen Runde, Lennart Vater, Lutz Eckstein:
The inD Dataset: A Drone Dataset of Naturalistic Road User Trajectories at German Intersections. IV 2020: 1929-1934 - [i11]Bastian Lampe, Raphael van Kempen, Timo Woopen, Alexandru Kampmann, Bassam Alrifaee, Lutz Eckstein:
Reducing Uncertainty by Fusing Dynamic Occupancy Grid Maps in a Cloud-based Collective Environment Model. CoRR abs/2005.02298 (2020) - [i10]Lennart Reiher, Bastian Lampe, Lutz Eckstein:
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. CoRR abs/2005.04078 (2020) - [i9]Daniel Becker, Fabian Ruß, Christian Geller, Lutz Eckstein:
Generation of Complex Road Networks Using a Simplified Logical Description for the Validation of Automated Vehicles. CoRR abs/2006.03403 (2020) - [i8]Laurent Kloeker, Christian Geller, Amarin Kloeker, Lutz Eckstein:
High-Precision Digital Traffic Recording with Multi-LiDAR Infrastructure Sensor Setups. CoRR abs/2006.12140 (2020) - [i7]Laurent Kloeker, Christian Kotulla, Lutz Eckstein:
Real-Time Point Cloud Fusion of Multi-LiDAR Infrastructure Sensor Setups with Unknown Spatial Location and Orientation. CoRR abs/2008.00801 (2020) - [i6]Daniel Bauer, Lars Kuhnert, Lutz Eckstein:
Deep Inverse Sensor Models as Priors for evidential Occupancy Mapping. CoRR abs/2012.02111 (2020) - [i5]Maike Scholtes, Lukas Westhofen, Lara Ruth Turner, Katrin Lotto, Michael Schuldes, Hendrik Weber, Nicolas Wagener, Christian Neurohr, Martin Bollmann, Franziska Körtke, Johannes Hiller, Michael Hoss, Julian Bock, Lutz Eckstein:
6-Layer Model for a Structured Description and Categorization of Urban Traffic and Environment. CoRR abs/2012.06319 (2020)
2010 – 2019
- 2019
- [c27]Jan Bavendiek, Emily Oliveira, Lutz Eckstein:
A Novel Method for Designing Metaphor-Based Driver-Vehicle Interaction Concepts in Automated Vehicles. AHFE (13) 2019: 15-26 - [c26]Minglu Li, Lutz Eckstein:
Fail-Operational Steer-By-Wire System for Autonomous Vehicles. ICVES 2019: 1-6 - [c25]Alexandru Kampmann, Bassam Alrifaee, Markus Kohout, Andreas Wüstenberg, Timo Woopen, Marcus Nolte, Lutz Eckstein, Stefan Kowalewski:
A Dynamic Service-Oriented Software Architecture for Highly Automated Vehicles. ITSC 2019: 2101-2108 - [c24]Johannes Hiller, Michael Schuldes, Lutz Eckstein:
Recognition and Pseudonymization of Data Privacy Relevant Areas in Videos for Compliance with GDPR. ITSC 2019: 2387-2393 - [c23]Robert Krajewski, Tobias Moers, Adrian Meister, Lutz Eckstein:
BézierVAE: Improved Trajectory Modeling using Variational Autoencoders for the Safety Validation of Highly Automated Vehicles. ITSC 2019: 3788-3795 - [c22]Daniel Bauer, Lars Kuhnert, Lutz Eckstein:
Deep, spatially coherent Inverse Sensor Models with Uncertainty Incorporation using the evidential Framework. IV 2019: 2490-2495 - [c21]Julian Bock, Philipp Nolte, Lutz Eckstein:
Continuously Improving Model of Road User Movement Patterns using Recurrent Neural Networks at Intersections with Connected Sensors. VEHITS 2019: 319-326 - [c20]Robert Krajewski, Tobias Moers, Lutz Eckstein:
VeGAN: Using GANs for Augmentation in Latent Space to Improve the Semantic Segmentation of Vehicles in Images From an Aerial Perspective. WACV 2019: 1440-1448 - [i4]Daniel Bauer, Lars Kuhnert, Lutz Eckstein:
Deep, spatially coherent Occupancy Maps based on Radar Measurements. CoRR abs/1903.12467 (2019) - [i3]Daniel Bauer, Lars Kuhnert, Lutz Eckstein:
Deep, spatially coherent Inverse Sensor Models with Uncertainty Incorporation using the evidential Framework. CoRR abs/1904.00842 (2019) - [i2]Julian Bock, Robert Krajewski, Tobias Moers, Steffen Runde, Lennart Vater, Lutz Eckstein:
The inD Dataset: A Drone Dataset of Naturalistic Road User Trajectories at German Intersections. CoRR abs/1911.07602 (2019) - 2018
- [j2]Christoph Stiller, Wolfram Burgard, Barbara Deml, Lutz Eckstein, Frank Flemisch:
Kooperativ interagierende Automobile. Autom. 66(2): 81-99 (2018) - [c19]Christian Roesener, Michael Harth, Hendrik Weber, Johanna Josten, Lutz Eckstein:
Modelling Human Driver Performance for Safety Assessment of Road Vehicle Automation. ITSC 2018: 735-741 - [c18]Robert Krajewski, Julian Bock, Laurent Kloeker, Lutz Eckstein:
The highD Dataset: A Drone Dataset of Naturalistic Vehicle Trajectories on German Highways for Validation of Highly Automated Driving Systems. ITSC 2018: 2118-2125 - [c17]Robert Krajewski, Tobias Moers, Dominik Nerger, Lutz Eckstein:
Data-Driven Maneuver Modeling using Generative Adversarial Networks and Variational Autoencoders for Safety Validation of Highly Automated Vehicles. ITSC 2018: 2383-2390 - [c16]Clemens Nietzschmann, Sebastian Klaudt, Christoph Klas, Devid Will, Lutz Eckstein:
Trajectory optimization for Car-Like Vehicles in Structured and Semi-Structured Environments. Intelligent Vehicles Symposium 2018: 504-510 - [i1]Robert Krajewski, Julian Bock, Laurent Kloeker, Lutz Eckstein:
The highD Dataset: A Drone Dataset of Naturalistic Vehicle Trajectories on German Highways for Validation of Highly Automated Driving Systems. CoRR abs/1810.05642 (2018) - 2017
- [c15]Christian Roesener, Johannes Hiller, Hendrik Weber, Lutz Eckstein:
How safe is automated driving? Human driver models for safety performance assessment. ITSC 2017: 1-7 - [c14]Johanna Josten, Teresa Schmidt, Ralf Philipsen, Lutz Eckstein, Martina Ziefle:
Privacy and initial information in automated driving - Evaluation of information demands and data sharing concerns. Intelligent Vehicles Symposium 2017: 541-546 - [c13]Sebastian Klaudt, Adrian Zlocki, Lutz Eckstein:
A-priori map information and path planning for automated valet-parking. Intelligent Vehicles Symposium 2017: 1770-1775 - 2016
- [j1]Jorg Gissing, Philipp Themann, Sidney Baltzer, Thomas Lichius, Lutz Eckstein:
Optimal Control of Series Plug-In Hybrid Electric Vehicles Considering the Cabin Heat Demand. IEEE Trans. Control. Syst. Technol. 24(3): 1126-1133 (2016) - [c12]Christian Roesener, Felix Fahrenkrog, Axel Uhlig, Lutz Eckstein:
A scenario-based assessment approach for automated driving by using time series classification of human-driving behaviour. ITSC 2016: 1360-1365 - [c11]Robert Krajewski, Philipp Themann, Lutz Eckstein:
Decoupled cooperative trajectory optimization for connected highly automated vehicles at urban intersections. Intelligent Vehicles Symposium 2016: 741-746 - 2015
- [c10]Philipp Themann, Jens Kotte, Dominik Raudszus, Lutz Eckstein:
Impact of positioning uncertainty of vulnerable road users on risk minimization in collision avoidance systems. Intelligent Vehicles Symposium 2015: 1201-1206 - 2014
- [c9]Philipp Themann, Robert Krajewski, Lutz Eckstein:
Discrete dynamic optimization in automated driving systems to improve energy efficiency in cooperative networks. Intelligent Vehicles Symposium 2014: 370-375 - [c8]Janek Hudecek, Lutz Eckstein:
Improving and simplifying the generation of reference trajectories by usage of road-aligned coordinate systems. Intelligent Vehicles Symposium 2014: 504-509 - [c7]Sidney Baltzer, Jorg Gissing, Peter Jeck, Thomas Lichius, Lutz Eckstein:
Integration of micro-CHP units into BEVs - Influence on the overall efficiency, emissions and the electric driving range. Intelligent Vehicles Symposium 2014: 1193-1198 - [c6]Jens Klimke, Philipp Themann, Christoph Klas, Lutz Eckstein:
Definition of an embedded driver model for driving behavior prediction within the DESERVE platform. ICSAMOS 2014: 343-350 - 2013
- [c5]Alexander Katriniok, Jan P. Maschuw, Frederic Christen, Lutz Eckstein, Dirk Abel:
Optimal vehicle dynamics control for combined longitudinal and lateral autonomous vehicle guidance. ECC 2013: 974-979 - [c4]Marc Wimmershoff, Christoph Klas, Adrian Zlocki, Lutz Eckstein:
Sensitivity analysis for model based fusion of camera systems with navigation data. Intelligent Vehicles Symposium 2013: 69-75 - 2012
- [c3]Philipp Themann, Lutz Eckstein:
Modular approach to energy efficient driver assistance incorporating driver acceptance. Intelligent Vehicles Symposium 2012: 1023-1028 - [c2]Mohamed Benmimoun, Andreas Pütz, Adrian Zlocki, Lutz Eckstein:
Effects of ACC and FCW on Speed, Fuel Consumption, and Driving Safety. VTC Fall 2012: 1-6
2000 – 2009
- 2009
- [c1]Bernhard Niedermaier, Stephan Durach, Lutz Eckstein, Andreas Keinath:
The New BMW iDrive - Applied Processes and Methods to Assure High Usability. HCI (11) 2009: 443-452
Coauthor Index
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