Model Validation and Scenario Selection for Virtual-Based Homologation of Automated Vehicles

Applied Sciences

卷:11

Bernhard Schick¹  Daniel Schneider¹  Daniel Watzenig²  Frank Diermeyer³  Stefan Riedmaier³ 

[1] Institute for Driver Assistance and Connected Mobility, Kempten University of Applied Sciences, Bahnhofstr. 61, 87435 Kempten, Germany;

[2] Institute of Automation and Control, Technical University of Graz, Inffeldgasse 21, 8010 Graz, Austria;

[3] Institute of Automotive Technology, Technical University of Munich, Boltzmannstr. 15, 85748 Garching bei München, Germany;

关键词: autonomous vehicles;    data analysis;    model validation;    safety assessment;    scenario extraction;    simulation;   

DOI  :  10.3390/app11010035

来源: DOAJ

【 摘 要 】

Due to the rapid progress in the development of automated vehicles over the last decade, their market entry is getting closer. One of the remaining challenges is the safety assessment and type approval of automated vehicles, as conventional testing in the real world would involve an unmanageable mileage. Scenario-based testing using simulation is a promising candidate for overcoming this approval trap. Although the research community has recognized the importance of safeguarding in recent years, the quality of simulation models is rarely taken into account. Without investigating the errors and uncertainties of models, virtual statements about vehicle safety are meaningless. This paper describes a whole process combining model validation and safety assessment. It is demonstrated by means of an actual type-approval regulation that deals with the safety assessment of lane-keeping systems. Based on a thorough analysis of the current state-of-the-art, this paper introduces two approaches for selecting test scenarios. While the model validation scenarios are planned from scratch and focus on scenario coverage, the type-approval scenarios are extracted from measurement data based on a data-driven pipeline. The deviations between lane-keeping behavior in the real and virtual world are quantified using a statistical validation metric. They are then modeled using a regression technique and inferred from the validation experiments to the unseen virtual type-approval scenarios. Finally, this paper examines safety-critical lane crossings, taking into account the modeling errors. It demonstrates the potential of the virtual-based safeguarding process using exemplary simulations and real driving tests.

【 授权许可】

Unknown