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ATZelectronics worldwide

Simulation of Dense Traffic Situations to Validate Autonomous Driving Functions

  • 01-11-2022
  • Development
Published in:
Authors
Christopher Körtgen
Jürgen Abel
Peter Menzel
Published in
ATZelectronics worldwide | Issue 11/2022

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Excerpt

The article delves into the simulation of dense traffic situations to validate autonomous driving functions, emphasizing the critical need for precise vehicle detection in close proximity. FEV outlines a method using GPS-controlled foam vehicles to safely replicate urban traffic conditions on a test site. The article describes the preparation, route planning, safety concepts, and results of these simulations, highlighting the challenges and solutions in detecting vehicles at short distances. It also discusses the evaluation of road user detection systems through specific scenarios, including lane changes and pedestrian encounters, and the use of differential GPS systems for precise measurement and repeatability. The findings underscore the importance of such simulations in the development of safe autonomous driving functions.
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previous article Cloud Intelligence and Collective Learning for Automated and Connected Driving
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Title
Simulation of Dense Traffic Situations to Validate Autonomous Driving Functions
Authors
Christopher Körtgen
Jürgen Abel
Peter Menzel
Publication date
01-11-2022
Publisher
Springer Fachmedien Wiesbaden
Published in
ATZelectronics worldwide / Issue 11/2022
Electronic ISSN: 2524-8804
DOI
https://doi.org/10.1007/s38314-022-1401-0

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    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, IPG Automotive GmbH/© IPG Automotive GmbH, HORIBA/© HORIBA, Outokumpu/© Outokumpu, Head acoustics GmbH/© Head acoustics GmbH, Gentex GmbH/© Gentex GmbH, Ansys, Yokogawa GmbH/© Yokogawa GmbH, Softing Automotive Electronics GmbH/© Softing Automotive Electronics GmbH, measX GmbH & Co. KG