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Automatic Traffic Scenario Conversion from OpenSCENARIO to CommonRoad

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arxiv 2305.10080 v2 pith:WBAWDGE2 submitted 2023-05-17 cs.RO cs.FLcs.SE

Yuanfei Lin , Michael Ratzel , Matthias Althoff This is my paper · ORCID
classification cs.ROcs.FLcs.SE
keywords commonroadopenscenarioconverterformatscenarioscenariosautonomousavailable
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Scenarios are a crucial element for developing, testing, and verifying autonomous driving systems. However, open-source scenarios are often formulated using different terminologies. This limits their usage across different applications as many scenario representation formats are not directly compatible with each other. To address this problem, we present the first open-source converter from the OpenSCENARIO format to the CommonRoad format, which are two of the most popular scenario formats used in autonomous driving. Our converter employs a simulation tool to execute the dynamic elements defined by OpenSCENARIO. The converter is available at commonroad.in.tum.de and we demonstrate its usefulness by converting publicly available scenarios in the OpenSCENARIO format and evaluating them using CommonRoad tools.

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  1. Scenario-Based Hierarchical Reinforcement Learning for Automated Driving Decision Making

    cs.RO 2025-06 conditional novelty 5.0 of 10

    SAD-RL, a hierarchical RL framework trained on synthetic and real-road highway scenarios, achieves over 69 percent goal-reaching rates across all test scenario types in simulation.

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