How best to get through an airport?

Airport passenger travelator

Air passengers will almost double in number by 2036. Just eighteen years from now, the International Air Transport Association (IATA) predicts 7.8 billion passengers will be taking to the skies annually.

While the aircraft industry will surely benefit from this boom, and is already anticipating advanced manufacturing, airports will also need to cater for increased traffic. How best to increase passenger capacity at airports? Airport simulation is an important tool for testing, development and operational management. Here we look at several real-world examples of simulation working for airports.

Passenger flow simulation at Frankfurt Airport

Fraport manages airports in India, Peru, Turkey, China, Brazil and other countries around the world, its home base, however, is Frankfurt, Germany.

Frankfurt Airport is a large international flight hub. When the Fraport faced constraints on expanding the airport infrastructure, it decided to develop a passenger traffic management system that could predict the number of people in terminals at different times. The aim was to reduce the number of queues, increase the efficient use of existing facilities, and improve the quality of passenger service.

Airport sunrise
Click to enlarge: Airport sunrise

Consultants from acp-IT created a simulation model for Fraport, with the result enabling several hours of passenger traffic forecasting from only a few minutes run-time. The simulations take into account the specific characteristics of the airport’s operations and capture passenger flows throughout the terminal buildings. Following the implementation of the model the airport successfully served its busiest ever month, with 5.5 million passengers passing through without problem. Take a look at the case study (with video).

Modeling passenger behavior at Paris Orly Airport

Orly is the second busiest airport in France. Most of the passengers passing through the airport are family groups, and this creates specific demands on the terminal infrastructure. In particular, there is a tendency for people to cluster, and the use of space needs to allow for this.

The management company and the customer of the modeling project, Paris Aéroport, wanted to find the optimal configuration for the security check area. It was necessary to decide the organization of inspection queues and the number of control points needed for comfortable passenger service.

The consultants simulated several different layouts for the control zones and, based on the data of flight movements, they predicted the number and behavior of passengers at the airport at different times and reflected this in the simulation model.

The airport simulation also considered the characteristics of passengers: for example, if a family is going through passport control, it should not leave the control zone until all members of the family have been checked.

In addition, the consultants tested the impact of bottlenecks on each layout. This enabled them to suggest changes that would help optimize the terminal space and prevent difficulties with the movement of passengers. This project and several related pedestrian flow simulation models can be found in Vladimir Koltchanov’s Pedestrian Simulation for Public Buildings presentation.

Determining the optimal number of personnel at Saint Petersburg’s Pulkovo airport

As part of some non-commercial research, the ITS Consulting team simulated the operation of Pulkovo Airport. In 2017, passenger traffic increased by 23% over the previous year. A development that may have contributed to the emergence of queues at the airport and the follow-on effects of delays and disruption to flight schedules.

Since operational planning at the airport is mostly manual, consultants proposed to automate the process with simulation modeling. The simulation they created considered the spatial characteristics of the terminal, the schedules of airplanes and workers, the uneven arrival of passengers, and the load on the service points, as well as the probability of disruption.

In the model, the consultants simulated the path of passengers from the entering the airport to boarding the plane. Capturing the whole route made it possible to optimize pedestrian flows by accurately redistributing the flows of passengers and reducing queues.

To determine the optimal number of employees at each stage of the security check, consultants used density maps. These showed the load on the check points and enabled the consultants to balance demand in real time, adding or reducing staff as needed. By combining the simulation model with working reality, the consultants were able to provide an effective tool for use in the operational management of the airport.

❔ Will airports get bigger and require better passenger management as we head towards almost 8 billion passenger flights or will more flights be direct between smaller airports? Have your say in the comments below?

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