AI Driven Yard Automation
Thematic Area: Next Generation Port
18) How might we ensure more accurate prime mover fleet scheduling, navigation and positioning through intelligent prediction and automation solutions to maximise yard productivity in increasingly autonomous container terminals?
BACKGROUND
Container terminals use horizontal transport equipment (e.g. prime movers, AGVs) to move containers between yard blocks and ship-to-shore cranes. Currently, the location of prime movers are tracked using GPS. However, GPS accuracy is compromised and unpredictable in yard environments due to signal deflection from metallic containers and yard stacking configurations. These may cause prime movers to arrive late, creating delays in terminal planning.
SIGNIFICANCE OF PROBLEM
Loss of productivity due to:
- Inaccurate GPS positioning causing prime movers to arrive late at designated blocks, disrupting Just-in-Time operations
- Scheduling systems operating with incorrect positional data
- Cascading delays affecting overall yard productivity and equipment utilisation
POTENTIAL MARKET SIZE
There are over 800 major container ports worldwide, of which, reportedly less than 10% of which had implemented a form of operational automation as of 2025.
EXISTING EFFORTS
• Relying on traditional GPS systems despite known limitations
• Manual interventions required address GPS and delays in yard movements
