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Analysis of Real World Sensor Behavior for Rising Fidelity of Physically Based Lidar Sensor Models

Rosenberger, Philipp and Holder, Martin Friedrich and Zirulnik, Marina and Winner, Hermann
Rosenberger, Philipp (ed.) :

Analysis of Real World Sensor Behavior for Rising Fidelity of Physically Based Lidar Sensor Models.
In: 2018 IEEE Intelligent Vehicles Symposium (IV), June 26-30, 2018, Changshu, Suzhou, China.
[Conference or Workshop Item], (2018)

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Item Type: Conference or Workshop Item
Title: Analysis of Real World Sensor Behavior for Rising Fidelity of Physically Based Lidar Sensor Models
Language: German
Abstract:

Safety validation tests of automated driving (AD) use simulated environments and perception sensor models. To achieve the level of fidelity needed for safety approval, such sensor simulations can be physically based. For formulating requirements for sensor models to be used in such test frameworks, the extent to which they must include physical effects should be determined. One approach is to clarify their relevance for following processing steps like object detection or mapping. But at first, an analysis is needed to determine, which effects are relevant and if they can be implemented at all. In this work, we focus on one lidar sensor and analyze its observable real world sensor behavior to derive the possible effects, physically based lidar sensor models can include. Consequently, we describe environmental parameters that could be considered to influence physically based lidar sensor models. By investigating the specifications given by the manufacturer with own measurements, we show that some of them should be implemented in a dynamic manner. In conclusion, we enable to formulate detailed requirements for sensor models, as their actual possible fidelity is presented.

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: 2018 IEEE Intelligent Vehicles Symposium (IV)
Event Location: Changshu, Suzhou, China
Event Dates: June 26-30, 2018
Date Deposited: 07 Aug 2019 13:01
Last Modified: 07 Aug 2019 13:01
DOI: 10.1109/IVS.2018.8500511
URN: urn:nbn:de:tuda-tuprints-88771
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/8877
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