This section is a state-of-the-art collection for the sensor model sub-library. When you clone this template to implement your own model, delete this entire section from the readme.
- Credible Simulation Process Framework from the German research project SET Level of the PEGASUS project family
- Credibility-Assessment-Framework incl. Credibility Development Kit from the European research project UPSIM incl. corresponding publication
- PMSF FMI Bench
- OSI Validator
- Eclipse OpenMCx incl. GitHub repo for connecting FMUs (a.k.a. co-simulation)
- SET Level Model Verification
- Object Based Generic Perception Model
- Reflection Based Radar Object Model
Authors | Date | Title | Link / Repo / Paper / DOI | Data Set | Modality | Facility | Funding |
---|---|---|---|---|---|---|---|
Huch et al. | 2023 | Quantifying the LiDAR Sim-to-Real Domain Shift: A Detailed Investigation Using Object Detectors and Analyzing Point Clouds at Target-Level | 10.1109/TIV.2023.3251650 | Sim2Real-DistributionAligned-Dataset | Lidar | Technical University of Munich | / |
Haider et al. | 2023 | Performance Evaluation of MEMS-Based Automotive LiDAR Sensor and Its Simulation Model as per ASTM E3125-17 Standard | 10.3390/s23063113 | / | Radar | Kempten University of Applied Sciences | VIVID |
Ngo | 2023 | A methodology for validation of a radar simulation for virtual testing of autonomous driving | 10.18419/opus-12703 | / | Radar | University of Stuttgart | Robert Bosch GmbH |
Rosenberger | 2023 | Metrics for Specification, Validation, and Uncertainty Prediction for Credibility in Simulation of Active Perception Sensor Systems | 10.26083/tuprints-00023034 | / | Generic (Lidar) | TU Darmstadt | ENABLE-S3, PEGASUS, SET Level, VVMethods |
Ngo et al. | 2021 | A Multi-Layered Approach for Measuring the Simulation-to-Reality Gap of Radar Perception for Autonomous Driving | 10.1109/ITSC48978.2021.9564521 | / | Radar | University of Stuttgart | Robert Bosch GmbH |
Schaermann | 2020 | Systematische Bedatung und Bewertung umfelderfassender Sensormodelle | mediaTUM | / | Generic (Lidar) | TU München | BMW AG |
Rosenberger et al. | 2019 | Towards a Generally Accepted Validation Methodology for Sensor Models - Challenges, Metrics, and First Results | TUprints | / | Generic | TU Darmstadt | PEGASUS |
Elster | 2023 | Introducing the Double Validation Metric for Radar Sensor Models | 10.21203/rs.3.rs-3088648/v1 | / | Radar | TU Darmstadt | VIVID |
Authors | Date | Title | Chapter(s) | Link / Repo / Paper / DOI | Modality? | Facility | Funding |
---|---|---|---|---|---|---|---|
Linnhoff | 2023 | Analysis of Environmental Influences for Simulation of Active Perception Sensors | Chapter 5 | 10.26083/tuprints-00023116 | Lidar | TU Darmstadt | SET Level, VVMethods |
Holder | 2021 | Synthetic Generation of Radar Sensor Data for Virtual Validation of Autonomous Driving | Chapters 4.2, 5.2, 6.2-6.4 | 10.26083/tuprints-00017545 | Radar | TU Darmstadt | SET Level, VVMethods |
Elster | 2023 | A Dataset for Radar Scattering Characteristics of Vehicles Under Real-World Driving Conditions: Major Findings for Sensor Simulation | - | 10.1109/JSEN.2023.3238015 | Radar | TU Darmstadt | VIVID |
- Weber, Rosenberger: Simulation Credibility Layers – Toward a Holistic Assessment, SET Level Final Event (October 2022)
- Schunk, Rosenberger: Validation of Test Infrastructure - From Cause Trees to a Validated System Simulation, VVM Half Time Event (March 2022)
Authors | Date | Title | Link / Repo / Paper / DOI | Standards? | Facility | Funding |
---|---|---|---|---|---|---|
Haider et al. | 10.2022 | Development of High-Fidelity Automotive LiDAR Sensor Model with Standardized Interfaces | 10.3390/s22197556 | FMI/OSI | HS Kempten | VIVID |
Guillard et al. | 22.09.2022 | Learning to Simulate Realistic LiDARs | 10.48550/arXiv.2209.10986 | / | Ecole polytechnique federale de Lausanne | Microsoft |
Rott | 05.04.2022 | Dynamic Update of Stand-Alone Lidar Model Based on Ray Tracing Using the Nvidia Optix Engine | 10.1109/ICCVE52871.2022.9743000 | OSI, obj | ViF Graz | COMET K2 |
Gusmão et al. | 18.11.2020 | Development and Validation of LiDAR Sensor Simulators Based on Parallel Raycasting | 10.3390/s20247186 | (optScan in Unity) | Pontifical Catholic University of Rio de Janeiro | Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil (CAPES)—Finance Code 001 |
Wang et al. | 07.07.2019 | Automatic Generation of Synthetic LiDAR Point Clouds for 3-D Data Analysis | 10.1109/TIM.2019.2906416 | (CARLA) | Dalian University of Technology, Dalian, China | / |
Yue et al. | 06.2018 | A LiDAR Point Cloud Generator: from a Virtual World to Autonomous Driving | 10.1145/3206025.3206080 | (DeepGTAV with Script Hook V) | University of California, Berkeley, Berkeley, CA, USA | NSF, Award 1645964, together with Berkeley Deep Drive |
Woods | 2015 | GLIDAR: a simple OpenGL LIDAR simulator | GitHub | OpenGL | West Virginia University | / |
Authors | Date | Title | Link / Repo / Paper / DOI | Standards? | Facility | Funding |
---|---|---|---|---|---|---|
Lindenmaier et al. | 01.2023 | Object-Level Data-Driven Sensor Simulation for Automotive Environment Perception | 10.1109/TIV.2023.3287278 | / | Budapest University of Technology and Economics | EU and Ministry of Innovation and Technology of Hungary |
Schwind et al. | 02.11.2022 | Virtual Sensor Validation for Automated and Connected Driving | 10.1007/s38311-022-1405-7 | / | TU Ilmenau | VIVID |
Reiter et al. | 10.2022 | (SET Level Radar Model) | OSI | FZI Karlsruhe | SET Level | |
Kesury | 05.2022 | RADAR MODELING FOR AUTONOMOUS VEHICLE SIMULATION ENVIRONMENT USING OPEN SOURCE | 10.7912/C2/2924 | / | Purdue University Indianapolis, Indiana | / |
Aust et al. | 16.05.2022 | A Data-driven Approach for Stochastic Modeling of Automotive Radar Detections for Extended Objects | IEEExplore | / | Mercedes Benz | VIVID |
Prinz et al. | 2021 | Automotive Radar Signal and Interference Simulation for Testing Autonomous Driving | 10.1007/978-3-030-71454-3_14 | / | BMW | / |
Authors | Date | Title | Link / Repo / Paper / DOI | Standards? | Facility | Funding |
---|---|---|---|---|---|---|
Linnhoff et al. | 10.2022 | Modular OSMP Framework | GitLab | FMI/OSI | TU Darmstadt | SET Level |
- Camera?
- Ultrasonic?
- Thermal Imaging?
- ???
Authors | Date | Title | Link / Repo / Paper / DOI | Modality? | Standards? | Facility | Funding |
---|---|---|---|---|---|---|---|
Linnhoff | 2023 | Analysis of Environmental Influences for Simulation of Active Perception Sensors | 10.26083/tuprints-00023116 | Lidar | OSI, FMI | TU Darmstadt | SET Level, VVMethods |
Linnhoff et al. | 2021 | Refining Object-Based Lidar Sensor Modeling — Challenging Ray Tracing as the Magic Bullet | 10.1109/JSEN.2021.3115589 | Lidar | OSI, FMI | TU Darmstadt | SET Level, VVMethods |
Holder | 2021 | Synthetic Generation of Radar Sensor Data for Virtual Validation of Autonomous Driving | 10.26083/tuprints-00017545 | Radar | OSI, FMI | TU Darmstadt | SET Level, VVMethods |