Framework for airport outbound passenger flow modelling

This paper focusses upon passenger flow issues within airport terminals and includes all activities occurring between curb-side and boarding. To improve passenger flow and associated planning activities, a simulation framework is developed using Discrete-Event Simulation (DES). The DES is built using ExtendSim V9.2 simulator software from Imagine That. The model can be used to evaluate the efficiency of the outbound operational processes including check-in, security screening, immigration & custom and boarding. It can also assist management to identify potential bottlenecks in the system. The main input of the model is the flight schedule. A case study of the Brisbane international airport was analysed

Objective Validation of Airport Terminal Architecture using Agent-based Simulations

This thesis explores how airport terminal architecture is tested before it is built. The purpose of testing is to make sure an architectural layout aligns with the rest of the airport’s systems. The design of a terminal is a long and expensive process that must accommodate tens of thousands of passengers every hour, the movement of logistics, and control of security. Evaluating spaces for that many people can be difficult to measure, which can result in architects relying on their intuition and experience to judge the impact of a layout for daily operations without objective validation. It is not practical for designers to build a complete airport to see how it works and make renovations after finding aspects that have poor performance. As a result, testing airports requires using mathematical models and simulations to validate how well different systems work together. Designers try to validate architectural layouts in airport terminals by using crowd simulations to approximate passenger behaviour. Existing research in civil engineering and computer science has shown how mathematical models can predict patterns of human activity in the built environment on a large scale. However, these simulations have primarily focused on either modelling passengers as a process flow or people in emergency building evacuation. As a result, existing agent navigation does not consider how passengers use the surrounding architecture for decision-making during daily airport interactions. When passengers enter a terminal for the first time, they can be unaware of what they need to do or how to get there. Instead, passengers rely on using their perception of the environment (the architecture) to inform them what to do. However, there currently are no methods that incorporate architectural perception to validate a building layout in these conditions. This thesis develops an agent-based simulation to validate how well architectural layouts align with the daily operations of an airport terminal. It quantifies the value of a spatial arrangement as a function of people’s interactions in a given space. The model approximates human behaviour based on statistics from existing crowd simulations. It uses spatial analysis, like the isovist and graph theory, for agent navigation and measuring architectural conditions. The proposal incorporates agent perception to provide feedback between people’s decision-making and the influence of the surrounding space. The thesis calculates architectural value using normalized passenger priorities based on typical processing and non-processing airport domains. The success of a terminal layout is dependent on the agent’s ability to complete airport processing and fulfill their priorities. The final value of an architectural layout is determined using statistical methods to provide a probability distribution of likely values. The proposed agent simulation and mathematical models are built using Unity software, which is used to perform several simulation tests in this thesis. Basic functional components of the simulation are validated using existing crowd modelling standards. Tests are also performed to illustrate how different agent perception and priorities influence the value of architectural spaces. Monte Carlo simulations are created for simple terminal layouts to illustrate how changing the floor plan of a security area affects the architectural value for departing passengers. Finally, the architectural values of two real airport terminals are compared against an established passenger experience survey in a basic simulation model. The results of the testing shows that the agent simulation can differentiate between different architectural conditions, within reason, depending on the passengers’ priorities

Domino D3.1 - Architecture definition

This deliverable presents the concept of operation of Domino. It includes a description of the systems, subsystems and processes that will be taken into account in the model, as well as the general scope of the model. For each of the mechanisms suggested to be modelled in the project, the deliverable provides a set of possible operational concepts and uptake/scope to be deployed

A holistic model of emergency evacuations in large, complex, public occupancy buildings

Evacuations are crucial for ensuring the safety of building occupants in the event of an emergency. In large, complex, public occupancy buildings (LCPOBs) these procedures are significantly more complex than the simple withdrawal of people from a building. This thesis has developed a novel, holistic, theoretical model of emergency evacuations in LCPOBs inspired by systems safety theory. LCPOBs are integral components of complex socio-technical systems, and therefore the model describes emergency evacuations as control actions initiated in order to return the building from an unsafe state to a safe state where occupants are not at risk of harm. The emergency evacuation process itself is comprised of four aspects - the movement (of building occupants), planning and management, environmental features, and evacuee behaviour. To demonstrate its utility and applicability, the model has been employed to examine various aspects of evacuation procedures in two example LCPOBs - airport terminals, and sports stadiums. The types of emergency events initiating evacuations in these buildings were identified through a novel hazard analysis procedure, which utilised online news articles to create events databases of previous evacuations. Security and terrorism events, false alarms, and fires were found to be the most common cause of evacuations in these buildings. The management of evacuations was explored through model-based systems engineering techniques, which identified the communication methods and responsibilities of staff members managing these events. Social media posts for an active shooting event were analysed using qualitative and machine learning methods to determine their utility for situational awareness. This data source is likely not informative for this purpose, as few posts detail occupant behaviours. Finally, an experimental study on pedestrian dynamics with movement devices was conducted, which determined that walking speeds during evacuations were unaffected by evacuees dragging luggage, but those pushing pushchairs and wheelchairs will walk significantly slower.Open Acces

Service network design for emerging modes in air transport: autonomous airport inter-terminal bus shuttle and air metro

Emerging modes of air transport such as autonomous airport shuttle and air taxi are potentially efficient alternatives to current transport practices such as bus and train. This thesis examines bus shuttle service within an airport and air metro as two examples of network design. Within an airport, the bus shuttle serves passengers between the terminals, train stations, parking lots, hotels, and shopping areas. Air metro is a type of pre-planned service in urban air mobility that accommodates passengers for intra- or inter-city trips. The problems are to optimise the service, and the outputs including the optimal fleet size, dispatch pattern and schedule. Based on the proposed time-space networks, the service network design problems are formulated as mixed integer linear programs. The heterogeneous multi-type bus fleet case and stochastic demand case are extended for the airport shuttle case, while a rolling horizon optimisation is adopted for the air metro case. In the autonomous airport inter-terminal bus shuttle case, a Monte Carlo simulation-based approach is proposed to solve the case with demand stochasticity, which is then further embedded into an "effective" passenger demand framework. The "effective" demand is the summation of mean demand value and a safety margin. By comparing the proposed airport shuttle service to the current one, it is found that the proposed service can save approximately 27% of the total system cost. The results for stochastic problem suggest estimating the safety margin to be 0.3675 times of the standard deviation brings the best performance. For the second case, the service network design is extended with a pilot scheduling layer and simulation is undertaken to compare the autonomous (pilot-less) and piloted service design. The results suggest that an autonomous air metro service would be preferable if the price of an autonomous aircraft is less than 1.6 times the price of a human-driven one. The results for rolling horizon optimisation suggest to confirm the actual demand at least 45 minutes prior to departure. Based on data from the Sydney (Australia) region, the thesis provides information directly relevant for the service network design of emerging modes of air transport in the city