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AI-based perception and prediction of a critical event as a first step for shadow mode testing of the ACC function

  • 2024
  • OriginalPaper
  • Chapter
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Abstract

We motivate the development of a shadow testing mode for the ACC function and realize a recurrent neural network that recognizes certain standard scenarios and predicts a critical event in each of these scenarios. This is a first step in setting up the entire AI-based shadow system which, in addition to the perception and prediction stage for edgy scenarios, comprises an automated comparison between simulated predictions of the actuators for a small temporal neighborhood of the critical event in actual driving and in shadow mode.

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Title
AI-based perception and prediction of a critical event as a first step for shadow mode testing of the ACC function
Authors
Oliver Grüßer
Ralf Hofmann
Julien Marcelot
Jose Antonio Zarate Ramos
Copyright Year
2024
DOI
https://doi.org/10.1007/978-3-658-44797-7_6
    Image Credits
    AVL List GmbH/© AVL List GmbH, dSpace, BorgWarner, Smalley, FEV, Xometry Europe GmbH/© Xometry Europe GmbH, The MathWorks Deutschland GmbH/© The MathWorks Deutschland GmbH, HORIBA/© HORIBA, Outokumpu/© Outokumpu, Gentex GmbH/© Gentex GmbH, Ansys, Yokogawa GmbH/© Yokogawa GmbH, Softing Automotive Electronics GmbH/© Softing Automotive Electronics GmbH, measX GmbH & Co. KG, Hirose Electric GmbH/© Hirose Electric GmbH