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This paper presents a demonstration of our PAAMS 2021 paper using data-driven analysis of airport terminal operations and An Agent-based Airport Terminal Operations Model Simulator (AATOM). The goal of this paper is to demonstrate and analyze the impact of the current COVID-19 and future pandemic-related measures on airport terminal operations and to identify plans that airport management agents can take into account to control the flow of passengers in a safe, efficient, secure and resilient way. To analyze the impact of the identified COVID-19 measures on the airport operations, the existing agent-based AATOM model was need to be modified in order to implement these measures. In this paper, we illustrate a demo of a developed simulator tool by investigating the effects of different degrees of physical distancing rules among agents on the performances of the airport. In the demo session the attendees will have the possibility to (i) work with the simulator tool on different relevant parameters regarding different sections and agents in the airport; (ii) view and analyze different performance indicator analyzers of the simulator., Aerospace Transport & Operations

Discretionary activities such as retail, food, and beverages generate a significant amount of non-aeronautical revenue within the aviation industry. However, they are rarely taken into account in computational airport terminal models. Since discretionary activities affect passenger flow and global airport terminal performance, discretionary activities need to be studied in detail. Additionally, discretionary activities are influenced by other airport terminal processes, such as check-in and security. Thus, discretionary activities need to be studied in relation to other airport terminal processes. The aim of this study is to analyze discretionary activities in a systemic way, taking into account interdependencies with other airport terminal processes and operational strategies used to manage these processes. An agent-based simulation model for airport terminal operations was developed, which covers the main handling processes and passenger decision-making with discretionary activities. The obtained simulation results show that operational strategies that reduce passenger queue time or increase passenger free time can significantly improve global airport terminal performance through efficiency, revenue, and cost., Aerospace Transport & Operations

This paper presents a demonstration of our PAAMS 2021 paper using data-driven analysis of airport terminal operations and An Agent-based Airport Terminal Operations Model Simulator (AATOM). The goal of this paper is to demonstrate and analyze the impact of the current COVID-19 and future pandemic-related measures on airport terminal operations and to identify plans that airport management agents can take into account to control the flow of passengers in a safe, efficient, secure and resilient way. To analyze the impact of the identified COVID-19 measures on the airport operations, the existing agent-based AATOM model was need to be modified in order to implement these measures. In this paper, we illustrate a demo of a developed simulator tool by investigating the effects of different degrees of physical distancing rules among agents on the performances of the airport. In the demo session the attendees will have the possibility to (i) work with the simulator tool on different relevant parameters regarding different sections and agents in the airport; (ii) view and analyze different performance indicator analyzers of the simulator., Air Transport & Operations

Discretionary activities such as retail, food, and beverages generate a significant amount of non-aeronautical revenue within the aviation industry. However, they are rarely taken into account in computational airport terminal models. Since discretionary activities affect passenger flow and global airport terminal performance, discretionary activities need to be studied in detail. Additionally, discretionary activities are influenced by other airport terminal processes, such as check-in and security. Thus, discretionary activities need to be studied in relation to other airport terminal processes. The aim of this study is to analyze discretionary activities in a systemic way, taking into account interdependencies with other airport terminal processes and operational strategies used to manage these processes. An agent-based simulation model for airport terminal operations was developed, which covers the main handling processes and passenger decision-making with discretionary activities. The obtained simulation results show that operational strategies that reduce passenger queue time or increase passenger free time can significantly improve global airport terminal performance through efficiency, revenue, and cost., Air Transport & Operations

Agent-based modelling and simulation has shown to be a suitable paradigm for analyzing complex airport systems, such as airport security checkpoints. The models can be used to analyze important airport terminal performance areas, such as security and efficiency. However, limited knowledge exists on how agent-based models can be used to aid airport managers in their decision making. The agent-based models allow to estimate the criteria of the alternatives of a decision problem, but without criteria weights and score aggregation, the alternatives can not be compared or ranked. The main branch of techniques to establish weights for multiple criteria such that a score can be aggregated for decisions is called multi-criteria decision making. Thus, integrating multi-criteria decision making methods with agent-based models is a method to provide decision support for airport managers. Therefore, this research aims to answer how multi-criteria decision making methods can be integrated with agent-based models to provide decision aid to airport terminal decision makers with the aim of improving security and efficiency. To answer this research question, a methodology was proposed which combines agent-based models, multi-criteria decision making, discrete choice models, and expert knowledge. The methodology is applied to a case study in which several alternatives of configuring personnel are available. The results show that efficiency focused operators, which have low accuracy, introduce most variance between best and worst alternatives. The best alternatives have efficiency focused operators placed on peak hours because they decrease the queue in the peak hours, while maximizing overall hit rate because less passengers pass per lane in peak hours compared to non-peak hours. For realistic variations of operator performance, operator placement is found to have a significant influence on security checkpoint performance., Aerospace Engineering

Agent-based modelling and simulation has shown to be a suitable paradigm for analyzing complex airport systems, such as airport security checkpoints. The models can be used to analyze important airport terminal performance areas, such as security and efficiency. However, limited knowledge exists on how agent-based models can be used to aid airport managers in their decision making. The agent-based models allow to estimate the criteria of the alternatives of a decision problem, but without criteria weights and score aggregation, the alternatives can not be compared or ranked. The main branch of techniques to establish weights for multiple criteria such that a score can be aggregated for decisions is called multi-criteria decision making. Thus, integrating multi-criteria decision making methods with agent-based models is a method to provide decision support for airport managers. Therefore, this research aims to answer how multi-criteria decision making methods can be integrated with agent-based models to provide decision aid to airport terminal decision makers with the aim of improving security and efficiency. To answer this research question, a methodology was proposed which combines agent-based models, multi-criteria decision making, discrete choice models, and expert knowledge. The methodology is applied to a case study in which several alternatives of configuring personnel are available. The results show that efficiency focused operators, which have low accuracy, introduce most variance between best and worst alternatives. The best alternatives have efficiency focused operators placed on peak hours because they decrease the queue in the peak hours, while maximizing overall hit rate because less passengers pass per lane in peak hours compared to non-peak hours. For realistic variations of operator performance, operator placement is found to have a significant influence on security checkpoint performance., Aerospace Engineering