scenario-characterization 0.2.23

Automated Scenario Characterization Toolkit.

ScenarioCharacterization

Note: This project is a work in progress.

A generalizable, automated scenario characterization framework for trajectory datasets.

Currently, this is a re-implementation of the scenario characterization approach introduced in SafeShift, as part of an internship project at StackAV.

Repository: github.com/navarrs/ScenarioCharacterization

This repository currently uses:

• uv as the package manager.
• Hydra for hierarchical configuration management.
• Pydantic for input/output data validation.

Installation

Install the package

uv pip install scenario-characterization

Install the package in editable mode

Clone the repository and install the package in editable mode:

git clone [e-mail]:navarrs/ScenarioCharacterization.git
cd ScenarioCharacterization
uv run pip install -e .

To install with Waymo dependencies (required for running the example), use:

uv run pip install -e ".[waymo]"

Documentation

• Organization: Overview of the Hydra configuration structure.
• Schemas: Guidelines for creating dataset adapters and processors that comply with the required input/output schemas.
• Characterization: Details on supported scenario characterization and visualization tools, and how to use them.
• Example: Step-by-step usage example using the Waymo Open Motion Dataset.

Citing

@INPROCEEDINGS{stoler2024safeshift,
  author={Stoler, Benjamin and Navarro, Ingrid and Jana, Meghdeep and Hwang, Soonmin and Francis, Jonathan and Oh, Jean},
  booktitle={2024 IEEE Intelligent Vehicles Symposium (IV)},
  title={SafeShift: Safety-Informed Distribution Shifts for Robust Trajectory Prediction in Autonomous Driving},
  year={2024},
  volume={},
  number={},
  pages={1179-1186},
  keywords={Meters;Collaboration;Predictive models;Robustness;Iron;Trajectory;Safety},
  doi={10.1109/IV55156.2024.10588828}}