Increasing passenger numbers and the continuous need to utilize existing capacity in the most efficient way possible are ongoing challenges for airports. In situations where passenger numbers decrease, efficiency must be maintained, and the over-allocation of resources must be avoided. Passenger processing is also evolving with the introduction of additional checkpoints, biometrics, and self-service facilities. To operate efficiently and maintain service levels, terminal operators need insight and guidance to manage passenger flows and plan resources effectively.
With the Passenger Flow Prediction solution, end-to-end passenger flows are simulated to provide the most accurate prediction of load at processing points over the next 24 hours, indicating when service level targets will not be met. Planned and real-time flight data, historical data, old and new passenger behavior patterns, terminal layout, and process point parameters are combined with pedestrian behavior algorithms and incorporated into an agent-based passenger simulation. The simulation runs continuously, and the predictions are updated based on real-time flight updates and changes in resource allocations.
Manage & predict
AMORPH.aero Flow Predictor enables proactive management of terminal operations by providing accurate, real-time predictions of passenger flow, queues, and waiting times at process points.
When changes in loads at process points are identified due to estimated times of arrival for flights being early or late, operations managers can respond proactively to avoid congestion by rerouting passengers or adjusting resource allocations.
Online Dashboards provide fast and convenient access to KPIs, operations views, and predictions. To assist with managing transfer flights, the connection time for each group of transfer passengers, along with the calculated transfer time, is displayed.
An essential benefit of performing agent-based passenger simulation is that the real transfer time can be calculated, considering all queuing effects, as well as the impact of passengers arriving at a service point before or after another group. In this way, compromised connections due to excessive time spent at process points can be identified, even though the passengers have adequate connection time.
Planning runs, including the parameters used and calculation bases, as well as the effects of changes in resources and infrastructure, are versioned and always available and visible. This enables close cooperation and collaborative decision-making between planners, operational staff, and other stakeholders. The focus remains on passengers, their behavior in the terminal, and the opportunities for improving operational and commercial performance.
Supported features include:
- Layout-based Planning. Terminal models are created to scale for accurate simulations with precise routes and travel distances.
- Agent-based PAX-behaviour-oriented pedestrian simulation model.
- Detailed, on-scale, multilevel terminal layout – editable by the customer. Maintain the model as layouts change and evolve.
- Support for different process point types (e.g. security check, border control, boarding-pass control). Specify the unique constraints of all process points for maximum accuracy.
- Support for different passenger transportation systems (e.g. elevators, automated stairs, shuttles). Incorporate the different travel speeds of each travel mode.
- Use of different distributions (e.g., Weibull, Normal) for simulation parameters (process times, walking speed, arrival rate) to refine your simulation.
- Dynamic capacity modelling. Consideration of changing capacity at service points, based on staff schedules.
- Adaptive resource capacity when the schedule is not available. Resource demand can be adapted in the absence of a schedule.
- Alternative PAX routes through the terminal. Include different routes in the model.
- APIs to integrate with local AODB / RMS. Ingest real-time operations data.
- API to share prediction results. Use prediction data in other Airport applications.
- Comparison with previous days. Compare scenarios with previous days to benefit from past scenarios.
- Advanced process time editor (distributions, hour of day, and PAX profiles)
- Integrate and display current flow measurements. Track predicted and actual measurements.
- Layout-based simulation. Terminal models are created to scale for accurate simulations with precise routes and travel distances.
- Waiting time and queue size prediction. Key measures are predicted to assist with planning optimization.
- Flow Steering. Passenger flows can be steered in different ways to balance resource loads.
- What-if Scenario analysis. Analyze and evaluate alternatives to optimize planning.
- Input for Resource / Staff Allocation Management. Provide planning inputs to resource management systems.
- Alerts & Notifications. Advise key personnel of potential bottlenecks.
- Accessible remotely and on mobile devices. Real-time access from any location for authorized users.