The present contribution introduces a systematic approach to the development of optimal attributes of Lane Keeping Assist Systems. An Active Lane Departure Warning (ALDW) with corrective steering interventions was the specific use case.

    Firstly, a subjective evaluation baseline was created from a proband study involving five different ALDW implementations and a catalogue of attribute related subjective rating criteria. Afterwards the respective vehicles were characterized by conducting designated driving maneuvers and computing objective performance indicators from the measurements taken. By correlating the subjective ratings with the performance indicators, a set of descriptive key performance indicators (KPIs) with corresponding target values was identified.

    Based on the objective targets an optimized calibration variant was prepared and implemented in a test vehicle. By repeating and evaluating the initial driving maneuvers, the coverage of targets was ensured. Conclusively proving the effectiveness of the introduced approach, a verification study under comparable conditions delivered significant subjective improvement as well.


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    Title :

    KPI-Based Attribute Development of Lane Keeping Assist Systems


    Additional title:

    Proceedings



    Conference:

    International Munich Chassis Symposium ; 2022 ; Munich, Germany July 05, 2022 - July 06, 2022



    Publication date :

    2024-04-30


    Size :

    15 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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