Upload README.md with huggingface_hub

README.md

@@ -28,19 +28,25 @@ size_categories:
 
 # EvenFlow Benchmark Dataset
 
-EvenFlow is a shared-space navigation evaluation suite built from real-world human trajectory data.
+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.
+**EvenFlow evaluates whether an agent can navigate *with* them.**
 
-This repository contains the benchmark data used to construct executable navigation tasks:
-- layouts
-- scenes
-- tasks
-- human trajectory tracks
+It converts real-world human trajectories into executable navigation tasks, enabling evaluation of **coordination, timing, and interaction—not just collision avoidance**.
 
-Code and evaluation tools are available at:
-https://github.com/standard-ai/evenflow-benchmark
+---
+
+## 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**.
 
 ---
 
@@ -48,41 +54,84 @@ https://github.com/standard-ai/evenflow-benchmark
 
 ```
 benchmark/
-  layouts/
   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:
+
+1. Load a task (`task.json`)
+2. Resolve its scene and associated human trajectories
+3. Run a planner to generate a **time-parameterized trajectory**
+4. 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.  
-Only anonymized trajectory data is released.
+The dataset reflects naturally occurring human behavior in shared spaces.
 
 ### Privacy
-No raw video, biometric identifiers, or personally identifiable information are included.
+
+- 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 on:
-- navigation in human environments
-- multi-agent coordination
-- trajectory-based evaluation
+
+This dataset is intended for research in:
+
+- robot navigation in human environments  
+- multi-agent coordination  
+- trajectory-based evaluation  
+- human-aware motion planning  
 
 ### Limitations
-- Single-site data collection
-- No demographic attributes
-- Offline evaluation setting
+
+- 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 license.
+This dataset is released under a custom research license.
 
-- Free for research and non-commercial use  
+- Free for research and academic use  
 - Commercial use requires a separate agreement  
 
-See LICENSE for details.
+See the LICENSE file for full terms.