Simulation-based test methods with an automotive camera-in-the-loop for automated driving algorithms

Reway, Fabio; Drechsler, Maikol Funk; Murthy, Ravikiran; Poledna, Yuri; Huber, Werner; Icking, Christian

doi:10.1109/iceccme55909.2022.9988437

Cited by 3 publications

(1 citation statement)

References 15 publications

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“…[ 119 ] Experimental results showed that the proposed method can quantify the performance of the tested detection algorithms, especially suitable in some severe weather conditions and some unwanted effects on the lenses. [ 120 ]…”

Section: Sensor Physical Signal Generation In Testbench‐based Vilmentioning

confidence: 99%

A Survey on Testbench‐Based Vehicle‐in‐the‐Loop Simulation Testing for Autonomous Vehicles: Architecture, Principle, and Equipment

Cheng,

Wang,

Zhao

et al. 2024

Advanced Intelligent Systems

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Autonomous vehicles (AVs) must be thoroughly tested to ensure safety and reliability before marketing. Simulation‐based testing has gained widespread recognition as the essential approach for AV testing by providing sufficient testing scenarios in the virtual environment. Vehicle‐in‐the‐loop (VIL) simulation has the ability to perform comprehensive tests and validations for the AVs’ overall behaviors while keeping significant testing accuracy and efficiency through the combination of the virtual scenarios and the physical AV. This article provides an overview of representative studies on testbench‐based VIL simulation testing for AVs, mainly focusing on utilizing testbenches to simulate realistic road conditions, and using physical signal stimulation methods and related equipment to generate sensors’ physical signals. This article first summarizes current AV testing studies, identifying existing issues and flaws of the state‐of‐the‐art methods and tools. Afterward, the testbench‐based VIL is addressed around architecture, principles, advantages, and characteristics. Then, the road condition simulation and the sensor physical signal generation in VIL are discussed in depth from structure, principle, and corresponding advanced equipment. Finally, research gaps between cutting‐edge technologies and AV testing applications in industrialization are identified to facilitate future research in this direction.

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Section: Sensor Physical Signal Generation In Testbench‐based Vilmentioning

confidence: 99%

A Survey on Testbench‐Based Vehicle‐in‐the‐Loop Simulation Testing for Autonomous Vehicles: Architecture, Principle, and Equipment

Cheng,

Wang,

Zhao

et al. 2024

Advanced Intelligent Systems

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Luminance Simulation in CARLA under Cloud Coverage - Model Validation and Implications

Ulreich,

Moser,

Olbrich

et al. 2023

2023 IEEE International Workshop on Metrology for Automotive (MetroAutomotive)

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Advanced Driver Assistance Systems Camera System Validation Using Open-Source Maps Data

Saddaladinne,

Pachaiyappan

2024

SAE Technical Paper Series

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<div class="section abstract"><div class="htmlview paragraph">Advanced Driver Assistance Systems (ADAS) is a growing technology in automotive industry, intended to provide safety and comfort to the passengers with the help of variety of sensors like radar, camera, Light Detection and Ranging (LIDAR) etc. The camera sensors in ADAS used extensively for the purpose of object detection and classification which are used in functions like Traffic sign recognitions, Lane detections, Object detections and many more. The development and testing of camera-based sensors involves the greater technologies in automotive industry, especially the validation of camera hardware and software. The testing can be done by various processes and methods like real environment test, model-based testing, Hardware, and Software in loop testing. A fully matured ADAS camera system in the market comes after passing all these verification processes, yet there are lot of new failures popping up in the field with this ADAS system. Since ADAS is an evolving technology, many new field issues keep coming due to huge diversity of features in the real-world infrastructure. So, to bring up a more reliable ADAS system, validating every newly reported issue and including the fix in the software is the only way to bring the safe and reliable system in the Automobiles. If there is any issue reported in certain places, the current practice is to reproduce the issue in the same place, analyzing the issue & finding the solution with fix in the software and finally validating that issue in the same location. This process of reproducing the issue & validating the fix in the same location can become more complex and expensive since that hotspot locations can be found anywhere in the world. This paper proposes a technique for the camera-based testing includes maps-based testing by using real maps scenarios played in front of the camera in controlled simulation environment and evaluate the results to confirm the software maturity. Real world scenarios can be created using open-source maps data and using it after fine tuning in the Hardware in Loop (HiL) system can reduce the complexity and cost of development & validation of ADAS camera Sensors.</div></div>

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Simulation-based test methods with an automotive camera-in-the-loop for automated driving algorithms

Cited by 3 publications

References 15 publications

A Survey on Testbench‐Based Vehicle‐in‐the‐Loop Simulation Testing for Autonomous Vehicles: Architecture, Principle, and Equipment

A Survey on Testbench‐Based Vehicle‐in‐the‐Loop Simulation Testing for Autonomous Vehicles: Architecture, Principle, and Equipment

Luminance Simulation in CARLA under Cloud Coverage - Model Validation and Implications

Advanced Driver Assistance Systems Camera System Validation Using Open-Source Maps Data

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