| name | geo-infer-transport |
| description | Transportation network analysis and traffic modeling. Use when analyzing road networks, simulating traffic (BPR model), forecasting traffic (EWMA), computing emissions, or optimizing transport routes. |
| prerequisites | {"required":["geo-infer-space","geo-infer-data"],"recommended":["geo-infer-math","geo-infer-time"]} |
| difficulty | intermediate |
| estimated_time | 45min |
| examples_dir | ../GEO-INFER-EXAMPLES/examples/ |
GEO-INFER-TRANSPORT
Instructions
Core Capabilities
- Traffic simulation: BPR (Bureau of Public Roads) microsimulation with V/C ratios
- Traffic forecasting: EWMA model with trend estimation and confidence intervals
- Network analysis: Critical link identification, connectivity metrics
- Emissions: Transportation emissions calculation (integrates with LOG)
- Route optimization: Multi-criteria route selection
Key Imports
from geo_infer_transport.core.traffic import simulate_traffic, forecast_traffic
from geo_infer_transport.core.network import TransportNetwork
from geo_infer_transport.core.routing import RoutingEngine
Examples
from geo_infer_transport.core.traffic import simulate_traffic
demand = {"matrix": [[100, 50], [30, 80]]}
result = simulate_traffic(demand, simulation_hours=1, time_step_seconds=15)
print(f"Completed trips: {result['statistics']['completed_trips']}")
Guidelines
simulate_traffic uses real BPR delay function (not hardcoded)forecast_traffic uses EWMA + trend estimation (not fake cyclic variation)- Emissions bridged from LOG module via optional import
- Test:
uv run python -m pytest GEO-INFER-TRANSPORT/tests/ -v
Integrations
- LOG → Emissions calculator and route optimization
- ECON → Transportation cost for trade flows
- EMERGENCY → Evacuation route planning
- HEALTH → Healthcare accessibility travel times
- SPACE → Road network spatial indexing
