The way to autonomous driving is closely connected to the capability of verifying and validating Advanced Driver Assistance Systems (ADAS), as it is one of the main challenges to achieve secure, reliable and thereby socially accepted self-driving cars. Hardware-in-the-Loop (HiL) based testing methods offer the great advantage of validating components and systems in an early stage of the development cycle, and they are established in automotive industry.When validating ADAS using HiL test benches, engineers face different barriers and conceptual difficulties: How to pipe simulated signals into multiple sensors including radar, ultrasonic, video, or lidar? How to combine classical physical simulations, e.g. vehicle dynamics, with sophisticated three-dimensional, GPU-based environmental simulations?In this article, we present current approaches of how to master these challenges and provide guidance by showing the advantages and drawbacks of each approach. Therefore, we discuss different ADAS setups and show ways of how to implement HiL test benches for these. We discuss two categories: 1) Hardware level: we focus on the communication structure between the simulated plant model and the Unit under Test (UuT). We show possible interfaces into the sensor units and involved bus systems. 2) Software level: we focus on how to provide the data the UuT expects. This results in rendering images, creating data lists or providing ray-tracing based point clouds.This article provides solutions for current and up-coming challenges when dealing with HiL-based validation of ADAS and presents an overview of current test-approaches.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Current Approaches in HiL-Based ADAS Testing


    Weitere Titelangaben:

    Sae Int. J. Commer. Veh


    Beteiligte:
    Haering, Juergen (Autor:in) / Feilhauer, Marius (Autor:in) / Wyatt, Sean (Autor:in)

    Kongress:

    SAE 2016 Commercial Vehicle Engineering Congress ; 2016



    Erscheinungsdatum :

    2016-09-27


    Format / Umfang :

    7 pages




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




    Current Approaches in HiL-Based ADAS Testing

    Feilhauer, Marius / Haering, Juergen / Wyatt, Sean | British Library Conference Proceedings | 2016


    AI ADAS AI BASED ADAS ROOM-MIRROR

    CHOI KWANG JOO | Europäisches Patentamt | 2021

    Freier Zugriff

    TARGET VEHICLE FOR ADAS TESTING

    BRIGHT WILLIAM / MARTIN COLIN / COCCO GABRIELE et al. | Europäisches Patentamt | 2021

    Freier Zugriff

    Target vehicle for ADAS testing

    BRIGHT WILLIAM / MARTIN COLIN / COCCO GABRIELE et al. | Europäisches Patentamt | 2024

    Freier Zugriff

    Fahrerloses ADAS-Testing - robotergestuetztes Testen

    Jaeger,H. / TBJ-Dynamische Messtechnik,DE | Kraftfahrwesen | 2012