Literature DB >> 34300426

Configurable Sensor Model Architecture for the Development of Automated Driving Systems.

Simon Schmidt1, Birgit Schlager2,3, Stefan Muckenhuber2,4, Rainer Stark5.   

Abstract

Sensor models provide the required environmental perception information for the development and testing of automated driving systems in virtual vehicle environments. In this article, a configurable sensor model architecture is introduced. Based on methods of model-based systems engineering (MBSE) and functional decomposition, this approach supports a flexible and continuous way to use sensor models in automotive development. Modeled sensor effects, representing single-sensor properties, are combined to an overall sensor behavior. This improves reusability and enables adaptation to specific requirements of the development. Finally, a first practical application of the configurable sensor model architecture is demonstrated, using two exemplary sensor effects: the geometric field of view (FoV) and the object-dependent FoV.

Entities:  

Keywords:  automated driving; configurable sensor model; functional decomposition; model reusability; sensor effects; sensor model architecture; virtual testing

Year:  2021        PMID: 34300426     DOI: 10.3390/s21144687

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  2 in total

1.  Development and Experimental Validation of an Intelligent Camera Model for Automated Driving.

Authors:  Simon Genser; Stefan Muckenhuber; Selim Solmaz; Jakob Reckenzaun
Journal:  Sensors (Basel)       Date:  2021-11-15       Impact factor: 3.576

Review 2.  A Survey on Modelling of Automotive Radar Sensors for Virtual Test and Validation of Automated Driving.

Authors:  Zoltan Ferenc Magosi; Hexuan Li; Philipp Rosenberger; Li Wan; Arno Eichberger
Journal:  Sensors (Basel)       Date:  2022-07-29       Impact factor: 3.847

  2 in total

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