scholarly journals Systemic Agent-Based Modeling and Analysis of Passenger Discretionary Activities in Airport Terminals

Aerospace ◽  
2021 ◽  
Vol 8 (6) ◽  
pp. 162
Author(s):  
Adin Mekić ◽  
Seyed Sahand Mohammadi Ziabari ◽  
Alexei Sharpanskykh
Keyword(s):  
Agent Based Modeling ◽  
Aviation Industry ◽  
Operational Strategies ◽  
Modeling And Analysis ◽  
Agent Based ◽  
Terminal Performance ◽  
Airport Terminal ◽  
Airport Terminals ◽  
Terminal Operations ◽  
Retail Food

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.

scholarly journals Determining the Number of Passengers for Each of Three Reverse Pyramid Boarding Groups with COVID-19 Flying Restrictions

Symmetry ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 2038
Author(s):  
Camelia Delcea ◽  
R. John Milne ◽  
Liviu-Adrian Cotfas
Keyword(s):  
Health Risk ◽  
Recent Literature ◽  
Agent Based Modeling ◽  
The Novel ◽  
Agent Based ◽  
Social Distancing ◽  
Relative Preference ◽  
Search Optimization ◽  
Airport Terminal ◽  
Novel Coronavirus

The onset of the novel coronavirus SARS-CoV2 has changed many aspects of people’s economic and social activities. For many airlines, social distancing has reduced airplane capacity by one third as a result of keeping the middle seats empty. Additionally, social distancing between passengers traversing the aisle slows the boarding process. Recent literature has suggested that the reverse pyramid boarding method provides favorable values for boarding time and passenger health metrics when compared to other boarding methods with social distancing. Assuming reverse pyramid boarding with the middle seats unoccupied, we determined the number of passengers to include in each of three boarding groups. We assumed that passengers use a jet-bridge that connects the airport terminal to the airplane’s front door. We used agent-based modeling and a stochastic simulation to evaluate solutions. A full grid search found an initial good solution, and then local search optimization determined the best solution based upon the airline’s relative preference for minimizing average boarding time and minimizing risks to previously seated passengers from later-boarding, potentially contagious passengers breathing near them. The resulting solution contained the number of passengers to place into each of the three boarding groups. If an airline is most concerned about the health risk to seated passengers from later boarding passengers walking near them, the best three-group reverse pyramid method adapted for social distancing will first board passengers with window seats in the rear half of the airplane, then will board passengers with window seats in the front half of the airplane and those with aisle seats in the rear half of the airplane, and finally will board the passengers with aisle seats in the front half of the airplane. The resulting solution takes about 2% longer to board than the three-group solution that minimizes boarding time while providing a 25% decrease in health risk to aisle seat passengers from later boarding passengers.

scholarly journals An Observation-Driven Agent-Based Modeling and Analysis Framework for C. elegans Embryogenesis

PLoS ONE ◽  
2016 ◽  
Vol 11 (11) ◽  
pp. e0166551 ◽  
Author(s):  
Zi Wang ◽  
Benjamin J. Ramsey ◽  
Dali Wang ◽  
Kwai Wong ◽  
Husheng Li ◽  
...  
Keyword(s):  
Agent Based Modeling ◽  
Analysis Framework ◽  
Modeling And Analysis ◽  
Agent Based ◽  
C Elegans

scholarly journals Applicability of an agent-based modeling concept to modeling of transportation phenomena

2002 ◽  
Vol 12 (2) ◽  
pp. 141-156 ◽  
Author(s):  
Shinya Kikuchi ◽  
Jongho Rhee ◽  
Dusan Teodorovic
Keyword(s):  
Traditional Approach ◽  
Financial Economic ◽  
Transportation Systems ◽  
Behavioral Pattern ◽  
Agent Based Modeling ◽  
Modeling And Analysis ◽  
Agent Based ◽  
Transportation Problems ◽  
Analysis Process ◽  
The Individual

Today's transportation problems are found in the complex interactions of social, financial, economic, political, and engineering issues. The traditional approach to analyzing transportation problems has been the top-down approach, in which a set of overall objectives is defined and specific parts are fitted in the overall scheme. The effectiveness of this analysis process has been challenged when many issues need to be addressed at once and the individual parts participants to decisions have greater autonomy. A factor contributing to this phenomenon is the greater opportunity and power for individual parts to communicate and to interact with one another. As a result, it has become increasingly difficult to predict or control the overall performance of a large system, or to diagnose particular phenomena. In the past decade, the concept of agent-based modeling has been developed and applied to problems that exhibit a complex behavioral pattern. This modeling approach considers that each part acts on the basis of its local knowledge and cooperates and/or competes with other parts. Through the aggregation of the individual interactions, the overall image of the system emerges. This approach is called the bottom-up approach. This paper examines the link between today's transportation problems and agent-based modeling, presents the framework of agent based modeling, notes recently used examples applied to transportation, and discusses limitations. The intent of this paper is to explore a new avenue for the direction of modeling and analysis of increasingly complex transportation systems.

Agent-Based Modelling and Simulation of Airport Terminal Operations Under COVID-19-Related Restrictions

2021 ◽  
pp. 214-228
Author(s):  
Gregory Sanders ◽  
S. Sahand Mohammadi Ziabari ◽  
Adin Mekić ◽  
Alexei Sharpanskykh
Keyword(s):  
Modelling And Simulation ◽  
Agent Based ◽  
Agent Based Modelling ◽  
Airport Terminal ◽  
Terminal Operations

scholarly journals Toward Baggage-Free Airport Terminals: A Case Study of London City Airport

2021 ◽  
Vol 14 (1) ◽  
pp. 212
Author(s):  
Yirui Jiang ◽  
Runjin Yang ◽  
Chenxi Zang ◽  
Zhiyuan Wei ◽  
John Thompson ◽  
...  
Keyword(s):  
Carbon Emission ◽  
Clustering Algorithm ◽  
Network Design Problem ◽  
Aviation Industry ◽  
Net Zero ◽  
Density Based Clustering ◽  
Airport Terminal ◽  
Zero Carbon ◽  
Airport Terminals

Nowadays, the aviation industry pays more attention to emission reduction toward the net-zero carbon goals. However, the volume of global passengers and baggage is exponentially increasing, which leads to challenges for sustainable airports. A baggage-free airport terminal is considered a potential solution in solving this issue. Removing the baggage operation away from the passenger terminals will reduce workload for airport operators and promote passengers to use public transport to airport terminals. As a result, it will bring a significant impact on energy and the environment, leading to a reduction of fuel consumption and mitigation of carbon emission. This paper studies a baggage collection network design problem using vehicle routing strategies and augmented reality for baggage-free airport terminals. We use a spreadsheet solver tool, based on the integration of the modified Clark and Wright savings heuristic and density-based clustering algorithm, for optimizing the location of logistic hubs and planning the vehicle routes for baggage collection. This tool is applied for the case study at London City Airport to analyze the impacts of the strategies on carbon emission quantitatively. The result indicates that the proposed baggage collection network can significantly reduce 290.10 tonnes of carbon emissions annually.

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