Simulated Urban Dynamics
SF-LIFE
A full simulated, noise-free, open-access movement dataset for the San Francisco Bay Area.
Needs-Driven Agendas
Agents don't just move randomly. Built on a Maslowian behavioral framework, daily schedules emerge dynamically based on needs for food, recreation, social interaction, and mandatory obligations like work or school.
Multi-Modal Kinematics
Agendas are translated into high-fidelity trajectories using the Valhalla routing engine. Agents seamlessly navigate OpenStreetMap infrastructure across 9 counties utilizing walking, biking, driving, bus, and rail modes based on GTFS data.
Synthesized Population Demographics
The simulated population is procedurally generated to reflect realistic urban distributions, accurately categorized by behavior, occupation, and vehicle access.
Occupation
- Workers ~53%
- Students ~24%
- Homemakers ~23%
Vehicle Access
- Car Owners 48.3%
- No Vehicle 40.6%
- Bicycle Only 11.1%
Core Data Included
- ✓ 1Hz Trajectory Records
- ✓ Semantic Activity Agendas
- ✓ OSM Road & Building Graphs
Scalable Sub-Datasets
Available in agent-centric and bucketed Parquet formats to support environments of all sizes.
| Sampling Rate | 15 Agents | 100 Agents | 1K Agents | 10K Agents | 500K Agents |
|---|---|---|---|---|---|
| 1 Second (1Hz) | 0.24 GB | - | - | - | 443.0 GB |
| 5 Seconds | - | 0.36 GB | 3.60 GB | 37.8 GB | - |
| 1 Minute | - | 0.06 GB | 0.67 GB | 2.70 GB | 6.20 GB |
| 10 Minutes | - | - | 0.07 GB | 0.08 GB | 1.70 GB |