Automotive industry is inclined towards connected, comfortable, environment friendly, efficient and smarter systems. Advanced Driver Assist System (ADAS) technology assist drivers to achieve a safer as well as better ride by automation and improvisation of the vehicular systems. With the advent of ADAS system, there is a significant focus not only in the development of Electronic Control Units (ECUs) and its features to cater to the emerging market but also on the information that could be displayed to meet the functional as well as safety requirements. This ADAS information display ensures timely notification to the driver with unique alerts that can be acoustic or visual. These systems should be tested thoroughly to ensure reliability as failures may impose severe risk on the OEM. Hardware in the loop testing has been largely adopted by industry against manual testing in lieu of the testing constraints imposed by the latter. This paper discusses on the existing test methods for ADAS information display system testing using HIL. It also details on the automation trends adopted and highlights the key challenges associated with the development as well as reusability of the conventional test methods. It discusses an Artificial Intelligence based strategy for automation of cluster objects teaching, evaluation and illustrates the adoption of the same for ADAS HIL testing and brings out the efficiency and benefits achieved by the proposed strategy.


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    Title :

    Coalesce of Artificial Intelligence into ADAS Hardware-In-the-Loop Testing


    Additional title:

    Sae Technical Papers


    Contributors:

    Conference:

    SAE WCX Digital Summit ; 2021



    Publication date :

    2021-04-06




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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