scenariocenter: Methods from Real-world Data to a Scenario Database
<|reference_start|>scenariocenter: Methods from Real-world Data to a Scenario Database: Scenario-based testing is a promising method to develop, verify and validate automated driving systems (ADS) since pure on-road testing seems inefficient for complex traffic environments. A major challenge for this approach is the provision and management of a sufficient number of scenarios to test a system. The provision, generation, and management of scenario at scale is investigated in current research. This paper presents the scenario database scenario.center ( https://scenario.center ) to process and manage scenario data covering the needs of scenario-based testing approaches comprehensively and automatically. Thereby, requirements for such databases are described. Based on those, a four-step approach is proposed. Firstly, a common input format with defined quality requirements is defined. This is utilized for detecting events and base scenarios automatically. Furthermore, methods for searchability, evaluation of data quality and different scenario generation methods are proposed to allow a broad applicability serving different needs. For evaluation, the methodology is compared to state-of-the-art scenario databases. Finally, the application and capabilities of the database are shown by applying the methodology to the inD dataset. A public demonstration of the database interface is provided at https://scenario.center .<|reference_end|>
@article{schuldes2024scenario.center:,
    title={scenario.center: Methods from Real-world Data to a Scenario Database},
    author={Michael Schuldes, Christoph Glasmacher, Lutz Eckstein},
    journal={arXiv preprint arXiv:2404.02561},
    year={2024},
    archivePrefix={arXiv},
    eprint={2404.02561},
    primaryClass={cs.SE}
}