How Schiphol is leveraging tech, design, data and AI-powered intelligence to redefine airport capacity and flow management
Royal Schiphol Group
Royal Schiphol Group built in-house AI-powered tools — Dynamic Time Slots, (Passenger) Flow Balancing, and Gate Planning Insights — to align passenger demand with security and gate capacity. Dynamic Time Slots lets passengers pre-book security check times, steering an average of 7.5% of passengers away from peak moments (up to 22% on critical days), with 99.6% of passengers waiting under 10 minutes. Flow Balancing uses real-time sensor data, predictive models and simulation (a digital twin) to steer passenger groups, preventing over 4,000 minutes of crowding in 2024. Gate Planning Insights uses machine learning to optimise gate stand planning and turnaround operations. Overall passenger satisfaction score is 4.4 out of 5.
Overview
Royal Schiphol Group built in-house AI-powered tools — Dynamic Time Slots, (Passenger) Flow Balancing, and Gate Planning Insights — to align passenger demand with security and gate capacity. Dynamic Time Slots lets passengers pre-book security check times, steering an average of 7.5% of passengers away from peak moments (up to 22% on critical days), with 99.6% of passengers waiting under 10 minutes. Flow Balancing uses real-time sensor data, predictive models and simulation (a digital twin) to steer passenger groups, preventing over 4,000 minutes of crowding in 2024. Gate Planning Insights uses machine learning to optimise gate stand planning and turnaround operations. Overall passenger satisfaction score is 4.4 out of 5.
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Inspect the highlighted sourceThe challenge
Schiphol had the ambition to offer a passenger journey without waiting times by perfectly aligning demand and capacity, while managing security checkpoint congestion, unpredictable passenger flows during crowding events, and gate stand planning and turnaround operations.
The solution
Royal Schiphol Group built in-house AI-powered tools: Dynamic Time Slots lets passengers pre-book a preferred security check time via Schiphol's app or website up to three days before departure, with an intelligent algorithm dynamically allocating slots based on flight date, flight number, planned capacity and historical show-up patterns; Flow Balancing uses real-time sensor data, predictive models and simulations (a digital twin approach) to steer passenger groups by flight, groups or time window; and Gate Planning Insights uses machine learning to optimise gate stand planning and turnaround operations.
Reported business value
Dynamic Time Slots steers an average of 7.5% of passengers away from peak moments, rising to 22% on critical days, resulting in 99.6% of passengers waiting under 10 minutes. Flow Balancing prevented over 4,000 minutes of crowding in 2024 alone. Overall passenger satisfaction score is 4.4 out of 5, and the approach also lowers staffing costs, minimises missed flights, and decreases passenger claims.
Sources
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