How Simulation based Test Methods will substitute the Proving Ground Testing?

Drechsler, Maikol Funk; Seifert, Georg; Peintner, Jakob; Reway, Fabio; Riener, Andreas; Huber, Werner

doi:10.1109/iv51971.2022.9827394

Cited by 7 publications

(1 citation statement)

References 13 publications

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“…Entire vehicles with all their subsystems can be tested on roller benches challenged by using virtual environment-based sensor spoofing or sensor simulation [29][30][31]. Mixed reality testing solutions with real-time connected but separated tested and target objects in space were also developed [32,33]. Digital twin technologies have started to be more common, and already, the classical proving ground-based testing approaches consider their usage [34].…”

Section: Introductionmentioning

confidence: 99%

Development and Functional Validation Method of the Scenario-in-the-Loop Simulation Control Model Using Co-Simulation Techniques

Toth,

Szalay

2023

Machines

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With the facilitated development of highly automated driving functions and automated vehicles, the need for advanced testing techniques also arose. With a near-infinite number of potential traffic scenarios, vehicles have to drive an increased number of test kilometers during development, which would be very difficult to achieve with currently utilized conventional testing methods. State-of-the-Art testing technologies such as Vehicle-in-the-Loop (ViL) or Scenario-in-the-Loop (SciL) can provide a long-term solution; however, validation of these complex systems should also be addressed. ViL and SciL technologies provide real-time control and measurement with multiple participants; however, they require enormous computational capacity and low-latency communication to provide comparable results with real-world testing. 5G (fifth-generation wireless) communication and Edge computing can aid in fulfilling these needs, although appropriate implementation should also be tested. In the current paper, a realized control model based on the SciL architecture was presented that was developed with real-world testing data and validated utilizing co-simulation and digital twin techniques. The model was established in Simcenter Prescan© connected to MATLAB Simulink® and validated using IPG CarMaker®, which was used to feed the simulation with the necessary input data to replace the real-world testing data. The aim of the current paper was to introduce steps of the development process, to present the results of the validation procedure, and to provide an outlook of potential future implementations into the state of the art in proving ground ecosystems.

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