Traffic Management¶
How robots share space and avoid conflicts.
Overview¶
Traffic management ensures robots navigate efficiently without collisions or deadlocks. It's critical for warehouse performance.
| Topic | Description |
|---|---|
| Capacity | Node and edge capacity limits |
| Congestion | Traffic buildup and measurement |
| Deadlock | Detection and prevention |
| Reservations | Space reservation systems |
The Traffic Problem¶
Shared Resources¶
Robots share limited space:
- Nodes: Discrete locations
- Edges: Paths between nodes
Conflicts¶
What happens when resources are contested:
Traffic Model¶
Capacity-Based¶
Each node and edge has maximum occupancy:
Collision Prevention¶
When at capacity:
- New robots wait
- Or reroute (if configured)
Traffic States¶
Free Flow¶
All robots move without delay:
Congested¶
Some delays occur:
Gridlock¶
Movement stops:
Traffic Visualization¶
Light Traffic¶
Moderate Traffic¶
Heavy Traffic¶
Traffic Management Strategies¶
Reactive¶
Respond to congestion:
- Wait when blocked
- Reroute when path congested
- Queue at destinations
Proactive¶
Prevent congestion:
- Reserve paths ahead
- Route around busy areas
- Coordinate movements
Hybrid¶
Combine approaches:
- Reserve critical sections
- React to unexpected congestion
- Balance efficiency and safety
Configuration Overview¶
traffic:
# Capacity limits
node_capacity_default: 1
edge_capacity_default: 1
# Congestion handling
wait_on_blocked: true
reroute_on_congestion: false
reroute_threshold: 3.0
# Deadlock prevention
deadlock_detection: true
deadlock_resolution: priority
Performance Impact¶
Throughput vs. Fleet Size¶
Throughput
│
│ ┌──── Congestion limit
│ /│
│ / │
│ / │
│ / │
│ / │
│ / │
│ / │
│ / │
│/ │
└─────────┴─────── Fleet Size
↑
Optimal size
Key Relationships¶
- More robots → More congestion
- Better traffic management → Higher optimal fleet size
- Poor layout → Lower congestion threshold