Airport Ground Access Reliability and Resilience of Transit Networks: a Case Study

Abstract Airport ground access is one of the key determinants influencing air travellers' airport choice. The continuous growth of air travel demand and the consequent induced road congestion have encouraged the development of efficient transit systems approaching the airport, thus promoting a modal shift from individual cars to greener transport alternatives. In addition, transit systems must be resilient and reliable to air travellers, since the cost of missing a flight is high. In this paper, resilience aspects of transit systems accessing airport areas are discussed and some indexes have been set up to estimate the transit network resilience. Three different transit systems to get to a large regional Italian airport (Automated People Mover, Airport Shuttle Bus, Bus Line) are modelled and the system resilience has been estimated for each scenario by using the proposed indexes

A discrete event simulation model for inbound baggage handling

Abstract Inbound baggage handling represents a crucial process among airport terminal's activities as it affects directly airport performance and passengers' service quality perception. It is important to make the inbound process as efficient as possible and to explore solutions to enhance the performance of the system, thus reducing passengers' waiting time at baggage carousels. The aim of this paper is to present a detailed discrete event model of inbound baggage handling at a large regional Italian airport. The simulation model allows to fully understand the whole process and to identify bottlenecks and critical operations. The model is validated by comparing the simulation results with real data

Airport Passenger Arrival Process: Estimation of Earliness Arrival Functions

Abstract Airport terminals are complex nodes where passengers are processed under limited capacity conditions. Congestion problems and delays are likely to occur, with negative impacts on customer satisfaction. To keep high quality levels, the knowledge of passengers' arrival patterns is a key factor. In this study, a methodology based on the use of Bar Coded Boarding Pass (BCBP) technologies has been proposed to estimate arrival rate functions for different types of passengers (Low Cost and Full Carrier passengers) and time of the day. The results obtained for a test case have been analysed and discussed

Impacts of unplanned aircraft diversions on airport ground operations

When an unplanned disruption causes the temporary closure of an airport, incoming flights are re-routed to one (or more) nearby ones. As a consequence, traffic in the alternate airport increases and the efficiency, punctuality and regularity of operations may be compromised. The purpose of this work is to determine the impacts on the alternate airport airside operations due to the presence of diverted flights. If the number of aircraft to be serviced increases, ground handling operators are subjected to an additional workload, probably resulting in delayed departures and knock-on delays. A discrete-event simulation model of both aircraft landing-and-takeoff (LTO) cycles and turnaround operations is built by using AnyLogic. The model is applied to the case study of Lisbon "Humberto Delgado" airport. When the number of incoming flights increases upon a certain threshold, departure delays spread over the day, which should call for emergency actions and contingency plans

How to cope with air transport disruptions: airport airside resilience and vulnerability

The efficiency of airport airside operations is often compromised by unplanned disruptive events of different kinds, such as bad weather, strikes or technical failures, which negatively influence the punctuality and regularity of operations, causing serious delays and unexpected congestion. They may provoke important impacts and economic losses on passengers, airlines and airport operators, and consequences may propagate in the air network throughout different airports. In order to identify strategies to cope with such events and minimize their impacts, it is crucial to understand how disruptive events affect airports’ performance. The research field related with the risk of severe air transport network disruptions and their impact on society is related to the concepts of vulnerability and resilience. The main objective of this project is to provide a framework that allows to evaluate performance losses and consequences due to unexpected disruptions affecting airport airside operations, supporting the development of a methodology for estimating vulnerability and resilience indicators for airport airside operations. The methodology proposed comprises three phases. In the first phase, airside operations are modelled in both the baseline and disrupted scenarios. The model includes all main airside processes and takes into consideration the uncertainties and dynamics of the system. In the second phase, the model is implemented by using a generic simulation software, AnyLogic. Vulnerability is evaluated by taking into consideration the costs related to flight delays, cancellations and diversions; resilience is determined as a function of the loss of capacity during the entire period of disruption. In the third phase, a Bayesian Network is built in which uncertain variables refer to airport characteristics and disruption type. The Bayesian Network expresses the conditional dependence among these variables and allows to predict the impacts of disruptions on an airside system, determining the elements which influence the system resilience the most

Recovery time and propagation effects of passenger transport disruptions

We propose a method to evaluate public transport network vulnerability. We study the evolution of the passenger Volume Over Capacity (VOC) ratio throughout the network to measure the spatial and temporal extent of the impacts caused by an unplanned service segment disruption. The VOC ratio provides an indication of the on-board travel comfort, an important level-of-service indicator, as well as reflects the residual capacity for absorbing additional demand. Because of the dynamic nature of public transport systems, disturbances propagate through the network in both time and space. Our modelling approach is able to capture transit system dynamics and quantify the extent to which the network exhibits spillover effects. We apply the method to the case of the rapid public transport system of Stockholm Sweden We demonstrate how the changes in network saturation and the corresponding recovery time can be quantified

Aircraft turnaround and industrial actions: how ground handlers' strikes affect airport airside operational efficiency

The efficiency of airport turnaround operations has often been compromised by various disruptive events out of the airlines' control, such as strikes, which negatively influence the punctuality and regularity of operations. The purpose of this work is to determine the loss of airport operational performance provoked by ground handlers' industrial actions. A discrete-event simulation model of both aircraft landing-and-takeoff (LTO) cycles and turnaround operations has been built by using AnyLogic. If the number of ground handler's operators decreases, turnaround operations require more time to be performed, resulting in delayed departures and knock-on delays. For the case study of Lisbon \u201cHumberto Delgado\u201d airport, turnaround time increases more than linearly with respect to the decrease of staff resources in service. When the number of operators decreases under a certain threshold, turnaround lengthening cannot be absorbed by buffer times and departure delays propagate in cascade over the day. This threshold should call for emergency actions and contingency plans

A methodological framework to evaluate the impact of disruptions on airport turnaround operations: a case study

none4noThe efficiency and quality of airport airside operations are frequently compromised by various, unexpected disruptive events such as bad weather conditions, lack of handling staff and/or resources, strikes, aircraft diversions or technical failures, which may reduce airport airside operating capacity and affect the punctuality and regularity of the operations. In particular, disruptive events could lead to a substantial deviation of aircraft operations from the schedule, by causing the reduction of the system capacity and, thus, increasing congestion and flight delays, which worsen the overall performance of the air transport system. In this paper, the effects of unexpected events, particularly magnitude and duration, affecting airport airside operations are estimated within a general framework based on an element-by-element approach, adopted for the detailed representation and simulation of aircraft airside operations. The impacts generated by airport airside unexpected disruptions are modelled by using a discrete-event simulation model, dealing with both aircraft landing-and-takeoff (LTO) cycles and turnaround operations, developed and applied to the test case of a large regional airport.mixedPostorino, Maria Nadia; Mantecchini, Luca; Malandri, Caterina; Paganelli, FilippoPostorino, Maria Nadia; Mantecchini, Luca; Malandri, Caterina; Paganelli, Filipp