pretty_name: EvenFlow Benchmark
license: other
task_categories:
- robotics
- other
tags:
- navigation
- human-robot-interaction
- trajectory-data
- multi-agent
- benchmarking
annotations_creators:
- no-annotation
source_datasets:
- original
language:
- en
size_categories:
- 1K<n<10K
EvenFlow Benchmark Dataset
EvenFlow is an evaluation suite for shared-space navigation, built from real-world human trajectory data.
Most benchmarks evaluate whether an agent can navigate around people.
EvenFlow evaluates whether an agent can navigate with them.
It converts real-world human trajectories into executable navigation tasks, enabling evaluation of coordination, timing, and interaction—not just collision avoidance.
Dataset Download.
git clone https://huggingface.co/datasets/standard-cognition/EvenFlow
What This Dataset Provides
The dataset consists of:
- Layouts: static environment geometry
- Scenes: human trajectory data over time
- Tasks: executable navigation problems derived from real behavior
- Tracks: time-indexed human trajectories
These components are structured to support trajectory-level evaluation of navigation planners.
Dataset Structure
benchmark/
aligned_flow/
tasks/
scenes/
layouts/
cross_flow/
tasks/
scenes/
layouts/
interaction_constrained/
tasks/
scenes/
layouts/
Each scenario family captures a different navigation regime:
- Aligned Flow: motion aligned with surrounding traffic
- Cross Flow: traversal across moving streams
- Interaction-Constrained: navigation shaped by local human interactions
How to Use This Dataset
EvenFlow is designed for executable evaluation, not just analysis.
Typical workflow:
- Load a task (
task.json) - Resolve its scene and associated human trajectories
- Run a planner to generate a time-parameterized trajectory
- Evaluate the result using EvenFlow metrics
Code and evaluation tools:
👉 https://github.com/standard-ai/evenflow-benchmark
Responsible AI Considerations
Data Collection
Data was collected in real-world environments using overhead camera systems.
The dataset reflects naturally occurring human behavior in shared spaces.
Privacy
- No raw video is released
- No biometric identifiers are included
- No personally identifiable information (PII) is present
All released data consists of anonymized trajectory representations.
Intended Use
This dataset is intended for research in:
- robot navigation in human environments
- multi-agent coordination
- trajectory-based evaluation
- human-aware motion planning
Limitations
- Data is collected from a single physical environment (v1 release)
- No demographic or identity-related attributes are included
- Evaluation is performed offline (no closed-loop interaction)
We view this dataset as a foundation for broader multi-environment and interactive benchmarks.
License
This dataset is released under a custom research license.
- Free for research and academic use
- Commercial use requires a separate agreement
See the LICENSE file for full terms.