One of the major causes of stress at the airport is congestion.

Airports around the world are reaching or are operating beyond their maximum capacity due to the growing number of passengers and cargoes. Measures are being taken to alleviate congestion, such as increasing the number of staff on ground or expanding airports. However, understanding human behavior, meaning, the actions people take depending on their attributes and information given, becomes important to tackle this problem at its core.

Professor Shingo Takahashi of the Department of Industrial and Management Systems Engineering at Waseda University and Fujitsu Laboratories Ltd. developed a new technology that automatically analyzes the factors leading to congestion based on the results of human behavior simulations.

Conventionally in this kind of analysis, experts used the results of large numbers of congestion prediction simulations to try and find the root cause of congestion, but this process overlooked potential causes due to human error from time to time and required the simulations to be evaluated one by one, which sometimes took several months.

"The new technology groups categories that have a certain degree of commonality, and expresses the characteristics of respective agents (which represents a diverse group of people) in a small number of combination categories without listing the results of movements and routes of tens or hundreds of thousands of agents individually through simulation-based modeling," explains Professor Takahashi.

"This makes it easier to discover the cause of congestion and answer the question of what sort of measures can be taken to change the mindset or actions of people with specific sets of attributes in a matter of just few minutes."

To evaluate its effectiveness, Professor Takahashi and Fujitsu applied this technology to a human behavior simulation developed in 2015 for analyzing countermeasures for congestion at an airport1. As a result, they discovered approximately four times as many causes of congestion in comparison to analysis by experts.

To be specific, in an analysis of congestion at security screening, the system found that passengers lining up at a specific check-in counter caused sudden congestion. The measures implemented according to the findings of the technology reduced the number of people waiting in line by one sixth than the measures proposed by experts. Additionally, the number of staff required to implement the measure was reduced by two thirds.

This technology enables a quick evaluation of measures to ameliorate congestion in commercial facilities, event venues and other locations that deal with congestion due to high attendance or urban centralization as well.

Professor Takahashi says that he hopes this technology will contribute to improving safety and comfort in our community.

Aspects of this technology were presented at the Winter Simulation Conference 2018, an international conference held in Gothenburg, Sweden on December 9-12.