Highly Parameterizable and Generic Perception Sensor Model Architecture

Perception sensor modeling is essential for the safety validation of automated driving systems in virtual environments. Nevertheless, the community lacks a methodical approach to derive requirements for such sensor models that enables a serious application for safety validation in the first place. This article provides a method to specify sensor models for the environmental perception of automated driving systems.The key of the approach is a collaborative collection of causeeffect chains as the basis for specification. With this collection at hand, a tabular form is introduced to extract the relevance of the effect chains to be modeled. Combined profound expert assessments in the table enable the test engineer to specify sensor models within a traceable decision-making process.This work received funding from SET Level and VVM of the PEGASUS project family, promoted by the German Federal Ministry for Economic Affairs and Energy based on a decision of the Deutsche Bundestag.

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Towards Serious Perception Sensor Simulation for Safety Validation of Automated Driving - A Collaborative Method to Specify Sensor Models

Linnhoff

Rosenberger

Schmidt

et al. 2021

2021 IEEE International Intelligent Transportation Systems Conference (ITSC)

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Highly Parameterizable and Generic Perception Sensor Model Architecture

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Towards Serious Perception Sensor Simulation for Safety Validation of Automated Driving - A Collaborative Method to Specify Sensor Models

Towards Serious Perception Sensor Simulation for Safety Validation of Automated Driving - A Collaborative Method to Specify Sensor Models

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