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Towards Realistic Evaluation of Collective Perception for Connected and Automated Driving

Volk, Georg (författare)
University of Tübingen, Faculty of Science, Embedded Systems Group, Department of Computer Science, Germany
Delooz, Quentin (författare)
Högskolan i Halmstad,Halmstad Embedded and Intelligent Systems Research (EIS)
Schiegg, Florian A. (författare)
Robert Bosch GmbH, Corporate Research, Connected Mobility Systems, Hildesheim, Germany
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Von Bernuth, Alexander (författare)
University of Tübingen, Faculty of Science, Embedded Systems Group, Department of Computer Science, Germany
Festag, Andreas (författare)
CARISSMA – Research and Test Center for Vehicle Safety, Ingolstadt, Germany; Fraunhofer Institute for Transportation and Infrastructure Systems IVI, Ingolstadt, Germany
Bringmann, Oliver (författare)
University of Tübingen, Faculty of Science, Embedded Systems Group, Department of Computer Science, Germany
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 (creator_code:org_t)
IEEE, 2021
2021
Engelska.
Ingår i: 2021 IEEE International Intelligent Transportation Systems Conference (ITSC). - : IEEE. - 9781728191423 - 9781728191416 - 9781728191430 ; , s. 1049-1056
  • Konferensbidrag (refereegranskat)
Abstract Ämnesord
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  • Collective perception in Vehicle-to-Everything (V2X) communications allows vehicles to exchange preprocessed sensor data with other traffic participants. It is currently standardized by ETSI as a second generation V2X communication service. The use of collective perception as a communication service for future fully autonomous driving requires a thorough evaluation and validation. Most of the previous work on collective perception has considered large scale-simulations with a focus on communications. However, the perception pipeline used for collective perception is equally important and must not be neglected or over-simplified. Also, to study collective perception in detail, large-scale field testing is practically infeasible. In this paper we extend an existing simulation framework with a realistic model for V2X communications and sensor-data based processing delays. The result is a simulation framework that incorporates the entire collective perception pipeline, which enables to comprehensively study sensor-based perception. We demonstrate the capabilities of this enhanced framework by analyzing the delay of each component involved in the perception pipeline. This allows a detailed insight in end-to-end delays and the age of information within the environmental model of autonomous vehicles. © 2021 IEEE.

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Inbäddad systemteknik (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Embedded Systems (hsv//eng)

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