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Scenario Mining in the Urban Domain: Exploiting the Topology of a Road Network for Maneuver Annotation and Scenario Extraction
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  • Lars Klitzke ,
  • Clemens Schicktanz ,
  • Kay Gimm ,
  • Carsten Koch ,
  • Frank Köster
Lars Klitzke
Germany Aerospace Center (DLR)

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Clemens Schicktanz
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Carsten Koch
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Frank Köster
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Abstract

Before Automated Vehicles (AVs) can enter the market, academic and industrial partners must tackle system homologation to ensure the functional safety of AVs. For that task, a scenario-driven approach has gained acceptance in recent years since it allows facing the overall system’s complexity. Real-world drivings are a valuable source of scenarios. However, their extraction and analysis are still the subjects of research. This work addresses this issue and proposes a novel methodology to extract routing scenarios on urban intersections. Therefore, trajectories are annotated with routing maneuvers using a semantically enriched road network and map matching for route backtracking. The accuracy of the approach and consistency of the methodology is evaluated with Brunswick’s inner-city ring and by extracting u-turn scenarios on the Application Platform for Intelligent Mobility (AIM) Research Intersection of the German Aerospace Center (DLR).