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  The Adv-nuSc dataset is a collection of adversarial driving scenarios generated by the SCS-PE framework, designed to evaluate the robustness of autonomous driving (AD) systems.
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  It builds upon the nuScenes validation set, introducing intentionally challenging interactions that stress-test AD models with aggressive maneuvers such as cut-ins, sudden lane changes, tailgating, and blind spot intrusions.
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- - **Affiliation:** SUN YAT-SEN University; Geely Auto
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  - **License:** [CC-BY-SA-4.0](https://creativecommons.org/licenses/by-sa/4.0/)
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  The Adv-nuSc dataset is a collection of adversarial driving scenarios generated by the SCS-PE framework, designed to evaluate the robustness of autonomous driving (AD) systems.
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  It builds upon the nuScenes validation set, introducing intentionally challenging interactions that stress-test AD models with aggressive maneuvers such as cut-ins, sudden lane changes, tailgating, and blind spot intrusions.
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+ - **Affiliation:** SUN YAT-SEN University
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  - **License:** [CC-BY-SA-4.0](https://creativecommons.org/licenses/by-sa/4.0/)
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