ScenarioCharacterization: A Modular Toolkit for Characterizing Safety across Trajectory Datasets

Abstract:We introduce ScenarioCharacterization, an open-source framework for automated, dataset-agnostic profiling of driving scenarios in trajectory datasets. Our framework is packaged as a modular, configuration-driven pipeline of three layers: a dataset adapter that maps custom datasets onto an open Scenario representation, a characterizer that performs feature extraction, behavior probing, and criticality scoring at scenario and agent levels, and an analysis layer for scenario visualization and feature, score, and probe analyses. Because the layers communicate only through Pydantic-validated schemas composed via configurations, a new dataset can easily plug in without rewriting the characterization and analysis stack. This technical report describes the design and APIs, shows example outputs on Waymo Open Motion, Argoverse2, and nuPlan, and discusses downstream uses of the approach. The framework is available at this https URL.

Robotics (cs.RO)

arXiv:2608.16041 [cs.RO]

(or arXiv:2608.16041v1 [cs.RO] for this version)

https://doi.org/10.48550/arXiv.2608.16041 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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