Conceptual and Computational Modelling of Coordination Mechanisms in Air Traffic Management

Aerospace Transport & Operation

Agent-Based Modelling for Security Risk Assessment

Security Risk Assessment is commonly performed by using traditional methods based on linear probabilistic tools and informal expert judgements. These methods lack the capability to take the inherent dynamic and intelligent nature of attackers into account. To partially address the limitations, researchers applied game theory to study security risks. However, these methods still rely on traditional methods to determine essential model parameters, such as payoff values. To overcome the limitations of traditional methods, we propose an approach which combines agent-based modelling with Monte Carlo simulations. Agent-based models allow more realistic representation of essential aspects and processes of socio-technical systems at cognitive, social and organisational levels. Such models can be used to estimate risks and parameters related to them. An application of the approach is illustrated by a case study of an airport security checkpoint.Aerospace Transport & Operation

An Agent-based Model to Study Compliance with Safety Regulations at an Airline Ground Service Organization

According to aviation statistics, most of the safety occurrenceshappen not in the air, but on the ground. Management of airlines and airportsoften consider failures to comply with safety-related regulations as importantcontributors to safety occurrences. To address the issue of compliance,approaches based on external regulation of the employees’ behavior wereproposed. Unfortunately, an externally imposed control is often not internalizedby employees and has a short-term effect on their performance. To achieve along-term effect, employees need to be internally motivated to adhere toregulations. To understand the role of motivation for compliance in groundservice organizations, in this paper a formal agent-based model is proposedbased on theories from social science with a wide empirical support. The modelincorporates cognitive, social, and organizational aspects. The model wassimulated and partially validated by a case study performed at a real airlineground service organization. The model was able to reproduce behavioralpatterns related to compliance of the platform employees in this study. Basedon the model, global sensitivity analysis was performed. The results of thisanalysis together with the simulation results were used to generaterecommendations to improve compliance.Aerospace Transport & Operation

Design of a Demand Responsive Transport service using Distributed Constraint Optimization for airport access

Accessibility is one of the key performance indicators in the evaluation of a multimodal transport system and, as a result, transport planning has become increasingly more oriented towards it. Demand Responsive Transport (DRT) services have been proposed as a measure for increasing accessibility of a Public Transit (PT) network by servicing users in inaccessible areas. Through multimodal planning and coordination, a DRT service can be integrated within the extended PT network and supply the network optimally. In the context of PT users headed toward airports, an integrated DRT service is proposed for those with extended first-mile connections. This service makes use of taxis to transport users to transit points of a dedicated train line supplying a major European airport. Ride-sharing is considered, while optimal order of service and transit points for modal change are determined. To capture the decentralized nature of matching taxis to users, a multi-agent-based algorithm based on Distributed Constraint optimization Problems (DCOPs) is developed. Real-time information about routes and fixed schedules of the PT network are extracted via a dedicated routing Application Programming Interface (API). Experiments validate the applicability of the proposed solution by reporting a decrease in users’ first-mile travel time that is approximately analogous to the modal share the service captures.Air Transport & Operation

An agent-based empirical game theory approach for airport security patrols

Airports are attractive targets for terrorists, as they are designed to accommodate and process large amounts of people, resulting in a high concentration of potential victims. A popular method to mitigate the risk of terrorist attacks is through security patrols, but resources are often limited. Game theory is commonly used as a methodology to find optimal patrol routes for security agents such that security risks are minimized. However, game-theoretic models suffer from payoff uncertainty and often rely solely on expert assessment to estimate game payoffs. Experts cannot incorporate all aspects of a terrorist attack in their assessment. For instance, attacker behavior, which contributes to the game payoff rewards, is hard to estimate precisely. To address this shortcoming, we proposed a novel empirical game theory approach in which payoffs are estimated using agent-based modeling. Using this approach, we simulated different attacker and defender strategies in an agent-based model to estimate game-theoretic payoffs, while a security game was used to find optimal security patrols. We performed a case study at a regional airport, and show that the optimal security patrol is non-deterministic and gives special emphasis to high-impact areas, such as the security checkpoint. The found security patrol routes are an improvement over previously found security strategies of the same case study.Aerospace Transport & Operation

Formal modelling and verification of a multi-agent negotiation approach for airline operations control

This paper proposes and evaluates a new airline disruption management strategy using multi-agent system modelling, simulation, and verification. This new strategy is based on a multi-agent negotiation protocol and is compared with three airline strategies based on established industry practices. The application concerns Airline Operations Control whose core functionality is disruption management. To evaluate the new strategy, a rule-based multi-agent system model of the AOC and crew processes has been developed. This model is used to assess the effects of multi-agent negotiation on airline performance in the context of a challenging disruption scenario. For the specific scenario considered, the multi-agent negotiation strategy outperforms the established strategies when the agents involved in the negotiation are experts. Another important contribution is that the paper presents a logic-based ontology used for formal modelling and analysis of AOC workflows.Interactive IntelligenceAerospace Transport & Operation

Formal and computational modeling of anticipation mechanisms of resilience in the complex sociotechnical air transport system

With ever-growing numbers of passengers and complexity of the air transport system, it becomes more and more of a challenge to manage the system in an effective, safe, and resilient manner. This is especially evident when disruptions occur. Understanding and improving resilience of the air transport system and its adaptive capacity to disruptions is essential for the system’s uninterrupted successful performance. Using theoretical findings from behavioral sciences, this paper makes the first steps towards formalization of the adaptive capacity of resilience of the air transport system with a particular focus on its ability to anticipate. To this end, an expressive logic-based language called Temporal Trace Language is used. The proposed approach is illustrated by a case study, in which anticipatory mechanisms are implemented in an agent-based airport terminal operations model, to deal with a disruptive scenario of unplanned and challenging passenger demand at the security checkpoint. Results showed that the timing of an adaptive action could have a significant influence on reducing the risk of saturation of the system, where saturation implies performance loss. Additionally, trade-off relations were obtained between cost, corresponding to the extra resources mobilized, and the benefits, such as a decrease in risk of saturation of the passenger queue.Aerospace Transport & Operation

Agent-based modelling and analysis of security and efficiency in airport terminals

Both security and efficiency are important performance areas of air transport systems. Several methods have been proposed to assess security risks and estimate efficiency independently, but only few of these methods identify relationships between security risks and efficiency performance indicators. To analyze security, efficiency, and the relationships relations between them, an agent-based methodology was proposed in this work. This methodology combines an agent-based security risk assessment approach with agent-based efficiency estimation. The methodology was applied to a case study that analyzes security regarding an Improvised Explosive Device (IED) attack, different commonly used efficiency performance indicators in the aviation domain, such as queuing time for passengers, and the relationships between them. Results showed that reducing security risks and improving efficiency were not always conflicting objectives. Reducing the number of passengers before the security checkpoint was found to be an effective measure to reduce security risks and improve efficiency aspects. Furthermore, results showed that airports should attempt to spread passengers across the available space as much as possible to reduce the impact of an IED attack.Aerospace Transport & Operation

Agent-based distributed planning and coordination for resilient airport surface movement operations

Airport surface movement operations are complex processes with many types of adverse events which require resilient, safe, and efficient responses. One regularly occurring adverse event is that of runway reconfiguration. Agent-based distributed planning and coordination has shown promising results in controlling operations in complex systems, especially during disturbances. In contrast to the centralised approaches, distributed planning is performed by several agents, which coordinate plans with each other. This research evaluates the contribution of agent-based distributed planning and coordination to the resilience of airport surface movement operations when runway reconfigurations occur. An autonomous Multi-Agent System (MAS) model was created based on the layout and airport surface movement operations of Schiphol Airport in the Netherlands. Within the MAS model, three distributed planning and coordination mechanisms were incorporated, based on the Conflict-Based Search (CBS) Multi-Agent Path Finding (MAPF) algorithm and adaptive highways. MAS simulations were run based on eight days of real-world operational data from Schiphol Airport and the results of the autonomous MAS simulations were compared to the performance of the real-world human operated system. The MAS results show that the distributed planning and coordination mechanisms were effective in contributing to the resilient behaviour of the airport surface movement operations, closely following the real-world behaviour, and sometimes even surpassing it. In particular, the mechanisms were found to contribute to more resilient behaviour than the real-world when considering the taxi time after runway reconfiguration events. Finally, the highway included distributed planning and coordination mechanisms contributed to the most resilient behaviour of the airport surface movement operations.Aerospace Transport & Operation

Analyzing airport security checkpoint performance using cognitive agent models

Modern airports operate under high demands and pressures, and strive to satisfy many diverse, interrelated, sometimes conflicting performance goals. Airport performance areas, such as security, safety, and efficiency are usually studied separately from each other. However, operational decisions made by airport managers often impact several areas simultaneously. Current knowledge on how different performance areas are related to each other is limited. This paper contributes to filling this gap by identifying and quantifying relations and trade-offs between the detection performance of illegal items and the average queuing time at airport security checkpoints. These relations and trade-offs were analyzed by simulations with a cognitive agent model of airport security checkpoint operations. By simulation analysis a security checkpoint performance curve with three different regions was identified. Furthermore, the importance of focus on accuracy for a security operator is shown. The results of the simulation studies were related to empirical research at an existing regional airport.Aerospace Transport & Operation