The 1:4 Ratio That Changes Everything
The fundamental economic advantage of autonomous construction equipment comes from a simple ratio: 1 operator supervising 3-4 machines instead of 1 operator per machine.
This isn't theoretical. CHINOU has demonstrated this ratio across 400+ production projects. But how does it actually work? This article provides a technical deep-dive into multi-machine fleet control.
The Traditional Model: 1:1
In conventional construction, the operator-to-machine ratio is fixed:
- 1 operator physically in each machine
- Direct control of hydraulics
- Continuous human attention required
- No way to scale beyond 1:1
To operate 10 excavators, you need 10 operators. No exceptions.
The Autonomous Model: 1:4
With autonomous equipment and fleet control:
- AI handles real-time execution
- Operator monitors and supervises
- Human attention distributed across machines
- Scalable to 1:3 or 1:4 depending on application complexity
To operate 10 excavators, you need 2-3 operator-supervisors.
The Fleet Control Dashboard
The operator supervises autonomous machines through a tablet-based fleet control dashboard. Here's what they see and do:
Real-Time Status
For each machine in the fleet:
- Location: GPS position on site map
- Task progress: Percentage complete, remaining volume
- System health: Sensor status, connectivity, alerts
- Fuel/battery: Energy state and estimated runtime
The dashboard presents this information at a glance, enabling rapid assessment of fleet status.
Task Assignment
The operator assigns work to machines:
- Define work zones: Areas where each machine will operate
- Set task parameters: Excavation depth, grading specifications
- Establish priorities: Which tasks are most urgent
- Sequence operations: Order of task completion
Once assigned, the AI handles execution. The operator doesn't control individual bucket movements — they manage tasks at a higher level.
AI Execution
When a machine receives a task assignment, the AI takes over:
- Path planning: Calculate optimal excavation patterns
- Obstacle avoidance: Detect and navigate around obstacles
- Material handling: Adjust for soil conditions
- Safety systems: Monitor for humans and hazards
The AI processes sensor data 30+ times per second, making real-time adjustments that no human could match for sustained periods.
Operator Intervention
The operator can intervene at any time:
- Remote takeover: Assume direct control of any machine
- Task modification: Change parameters or redirect work
- Stop commands: Halt any or all machines immediately
- Mode switching: Toggle between autonomous, semi-auto, and manual
This intervention capability is always available, never more than one tap away.
The Operator's Workflow
A typical shift for an operator-supervisor looks different from traditional operation:
Morning Setup (15-30 minutes)
- Review site conditions and daily plan
- Assign initial tasks to each machine
- Verify all systems operational
- Start autonomous operations
Active Monitoring (Bulk of shift)
- Monitor dashboard for alerts or anomalies
- Adjust task parameters as conditions change
- Coordinate with site personnel
- Document progress
The operator isn't constantly controlling machines — they're monitoring and managing, intervening only when needed.
Interventions (As needed)
When intervention is required:
- Machine encounters unexpected obstacle → Review situation, clear or redirect
- Task completed → Assign next task
- Weather/site condition change → Adjust operations
- Personnel in work zone → Pause affected machines
Interventions are typically brief, allowing the operator to quickly return to fleet-wide monitoring.
End of Shift
- Park machines or hand off to next operator
- Review daily productivity data
- Note any issues for follow-up
Safety Architecture
Multi-machine control requires robust safety systems:
Multiple Layers
- AI perception: Continuous environment monitoring
- Automatic stop: Any anomaly triggers immediate stop
- Operator override: Human can stop any machine instantly
- Site integration: Coordination with site safety systems
Fail-Safe Design
The system is designed to fail safe:
- Communication loss → Machine stops
- Sensor degradation → Machine stops
- Obstacle detection → Machine stops
- Operator command → Immediate stop
No single point of failure can cause unsafe operation.
Human in the Loop
Despite high autonomy, a human operator is always in the loop:
- Monitoring all operations
- Available to intervene
- Making high-level decisions
- Accountable for safety
This is supervised autonomy, not unsupervised operation.
Technical Requirements
Multi-machine control requires specific technical capabilities:
Connectivity
- Cellular + backup: Multiple communication paths
- Low latency: Quick response for interventions
- Site coverage: Connectivity across work area
Dashboard Device
- Tablet or laptop: Portable for site mobility
- Outdoor display: Readable in daylight
- Touch interface: Quick interactions
Site Infrastructure
- Geofencing: Defined work zones
- Personnel tracking: Integration with safety systems
- Communication network: Site-wide coverage
Learn more about the full technology stack and how installation works.
Productivity Results
Multi-machine control delivers measurable productivity improvements:
Labor Efficiency
- 60%+ workforce reduction for excavation operations
- Same or better excavation output
- Higher skilled operator-supervisor roles
Utilization
- 24/7 operation capability (machines don't need sleep)
- 85% utilization achievable vs. 60% typical
- Night operation at no additional labor cost
Quality
- Consistent execution without fatigue variability
- Precise grading through AI control
- Reduced rework from errors
Getting Started with Multi-Machine Control
For companies interested in multi-machine fleet control:
1. Pilot Scale
Start with 3-5 machines:
- Learn the operational model
- Train operator-supervisors
- Validate productivity in your environment
2. Operator Training
Training focuses on:
- Dashboard operation
- Task assignment and management
- Intervention protocols
- Safety procedures
Training is included with pilot programs.
3. Scale Based on Results
Expand based on pilot performance:
- Add machines as confidence builds
- Develop internal expertise
- Optimize for your specific operations
Request a pilot to experience multi-machine control firsthand.
Conclusion
The 1:4 operator-to-machine ratio isn't a future possibility — it's a current reality deployed across 400+ projects. Multi-machine fleet control transforms the economics of construction operations.
One operator. Four machines. Same output. 75% fewer operators needed.
That's the change that autonomous equipment brings to construction.
Ready to see multi-machine control in action? Request a demo or learn more about how the technology works.