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Benchmarking and Functional Decomposition of Automotive Lidar Sensor Models

Rosenberger, Philipp and Holder, Martin Friedrich and Huch, Sebastian and Winner, Hermann and Fleck, Tobias and Zofka, Marc René and Zöllner, Johann Marius and D'Hondt, Thomas and Wassermann, Benjamin :
Benchmarking and Functional Decomposition of Automotive Lidar Sensor Models.
In: 2019 IEEE Intelligent Vehicles Symposium (IV), June 9-12, 2019, Paris, France.
[Conference or Workshop Item], (2019)

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Item Type: Conference or Workshop Item
Title: Benchmarking and Functional Decomposition of Automotive Lidar Sensor Models
Language: German
Abstract:

Simulation-based testing is seen as a major requirement for the safety validation of highly automated driving. One crucial part of such test architectures are models of environment perception sensors such as camera, lidar and radar sensors. Currently, an objective evaluation and the comparison of different modeling approaches for automotive lidar sensors are still a challenge. In this work, a real lidar sensor system used for object recognition is first functionally decomposed. The resulting sequence of processing blocks and interfaces is then mapped onto simulation methods. Subsequently, metrics applied to the aforementioned interfaces are derived, enabling a quantitative comparison between simulated and real sensor data at different steps of the processing pipeline. Benchmarks for several existing sensor models at a concrete selected interface are performed using those metrics by comparing them to measurements gained from the real sensor. Finally, we outline how metrics on low-level interfaces can correlate with results on more abstract ones. A major achievement of this work lies within the commonly accepted interfaces and a common understanding of real and virtual lidar sensor systems and, even more important, an initial guideline for the quantitative comparison of sensor models with the ambition to support future validation of virtual sensor models.

Classification DDC: 600 Technik, Medizin, angewandte Wissenschaften > 620 Ingenieurwissenschaften
Divisions: 16 Department of Mechanical Engineering
16 Department of Mechanical Engineering > Institute of Automotive Engineering (FZD)
16 Department of Mechanical Engineering > Institute of Automotive Engineering (FZD) > Driver Assistance
16 Department of Mechanical Engineering > Institute of Automotive Engineering (FZD) > Safety
16 Department of Mechanical Engineering > Institute of Automotive Engineering (FZD) > Test Methods
Event Title: 2019 IEEE Intelligent Vehicles Symposium (IV)
Event Location: Paris, France
Event Dates: June 9-12, 2019
Date Deposited: 18 Sep 2019 13:19
Last Modified: 18 Sep 2019 13:19
DOI: 10.1109/IVS.2019.8814081
URN: urn:nbn:de:tuda-tuprints-90601
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/9060
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