Modelling Passenger Flow at King Abdul-Aziz International Airport Using Any Logic - Thesis Proposal Example

Modelling passenger flow at King Abdul-Aziz International Airport using AnyLogic – a comparison between pedestrian and process based modelling approaches [ your name ] [ university name ] Master’s thesis submitted in partial fulfillment of [ degree name ] [ date ] Introduction Airports have emerged as a major feature of metropolises. Rising traffic levels at airports have led to scientific methods of investigation to deal with traffic control of pedestrians inside airports. Better pedestrian traffic design inside airports provides for optimal use of available resources and allows for improved deployment of new designs. On the other hand, customer experience facilitated by optimal use of deployed resources allows for greater economic efficiency of new airports (Regmi). This paper will investigate pedestrian traffic flows inside the newly designed King Abdulaziz Airport in Jeddah that is designed to handle around 30 million passengers per year (adpi). Passenger activities at airports are dynamic in nature – passengers may choose a number of options based on personal preferences. This in turn leads to multiple configurations for passenger traffic that must simultaneously cater to myriad problem constraints for providing an optimal passenger experience. The current research will focus on the major activities alone within the main airport terminal such as checking in, immigration control and police check point passenger flow. Auxiliary passenger activities such as accessing duty free shops, eateries and the like are beyond the scope of the current research. Background to Study The King Abdulaziz Airport was initially commissioned in 1981 to handle both local and international traffic. The airport is located at Jeddah, roughly between the holy cities of Mecca and Medina. Saudi Arabia’s expansion of air passenger traffic for both local and international air traffic routes has meant that expansion was desirable (adpi). The overarching aim of expansion at the King Abdulaziz Airport is to cater to a passenger inflow of 80 million per year (King Abdulaziz International Airport). The recent spate of expansion at the King Abdulaziz Airport has been designed to handle 30 million passenger versus the existing 13 million passenger, half of which are local and the other half international passengers. This corresponds to processing 3,800 arriving passengers per hour and 3,500 departing passengers per hour (International Finance Corporation). The King Abdulaziz Airport serves as one of the busiest air hubs in the region, especially during pilgrimage season when passengers to Mecca are received through this airport. Since its inception, the King Abdulaziz Airport has had to handle larger passenger volumes for pilgrimage journeys every year. The lack of appropriate expansion has meant that existing facilities are overburdened and waiting time has increased due to inefficient processing of passengers (International Finance Corporation). Some improvements to the main airport terminal have resulted in faster processing times and lower waiting. King Abdulaziz Airport was able to serve 6.2 million pilgrimage passengers in 2010 alone (International Finance Corporation). The next phase of expansion that plans to add a north and south terminal needs to be examined to determine what measure of performance improvement it entails. Modeling and Simulation Real world problems can be modeled and solved using computing techniques versus solutions generated through manual calculations offered by analytical solutions (Strogatz). The utilization of computing platforms offers ease of problem representation and solution as well as the representation of such solutions. One potent method of creating such solutions is through computer simulations that solve modelled problems. This offers the advantage of obtaining real world problem’s solutions without the need of creating physical models and performing expensive solution routines. Modern computing platforms offer the ease of modelling real world problems in various dimensions and obtaining solutions to see if the proposed schemes offer valid resolution. Computer simulations also provide the benefit of visualizing both problem formulation and problem solutions, which makes it simpler to assess and implement such solutions (Santner, Williams and Notz). Major Approaches to Computer Modeling and Simulation Computer modeling and simulation to solve real world problems related to passenger traffic flows could be achieved through system dynamic (SD), agent based (AB), discrete event (DE) and similar techniques. The SD approach to problem formulation and solution relies on internal feedback loops coupled to time delays which in turn affect the overall system’s behavior. The use of feedback loops in the SD approach provides for an appreciation of non-linearity, available in but not displayed at the outset by most complex systems (MIT). For example, for the case of passenger traffic flow inside an airport terminal, the SD approach would require internal feedback loops consisting of feedback from the passengers. Moreover, time delays would be catered for the time use of passengers for different activities inside the airport terminal such as immigration checking, police checking etc. In contrast, the AB approach to problem formulation and solution relies on depicting the overall system as the interaction of autonomous agents. The actions of the agents and their resulting outcomes on the system are analyzed to see how each agent tends to influence the system outcomes. It must be taken to note that an autonomous agent may be an individual or a group of individuals taken as an agent (Grimm and Railsback). For example, in the case of the current research, individual passengers are seen as autonomous agents for the modeling and simulation. The actions of each autonomous agent and its results on the overall system are analyzed to decipher how the system works. This allows an appreciation of how the airport terminal is configured to handle the increasing volumes of passenger traffic. On another note, AB based approach to modeling and simulating passenger traffic flow in an airport terminal would not necessarily require parallel processing of agent activities since an autonomous agent can only perform one activity in a period of time. The lengths of these periods of time may vary but the sequence of the involved activities would remain the same nonetheless. The DE technique for simulation banks on breaking down various systemic activities as a series of different events that are sequenced in time. Each varying event is assumed to have an impact on the system’s overall state. For simple DE systems, each event is seen to occur consecutively and it is generally assumed that between each systemic event, there are no changes of state. This approach, although greatly simplified, allows for generalization of the problem and allows an easier solution since the system solution is generated between consecutive systemic events (Robinson). It has to be kept in mind that such a simulation technique is opposed to the continuous simulation model where system dynamics change in continuity over a period of time. This also provides another advantage to the DE approach when solving problems – DE simulations are typically faster than comparable continuous simulation problem formulation and solutions (Matloff). For example, for the current research, passenger activities at the airport terminal would be taken as discrete events that are lined up consecutively. This model is all the more appropriate since airport terminal activities such as immigration checks, customs checks, police checks etc. are sequentially lined up discrete events. It could be argued that the length of these events would tend to vary from passenger to passenger but it must be realized that a discrete minimum time and a discrete maximum time could still be used to describe these events. Research Objective The objective of the current study is to develop two different passenger flow models for the King Abdulaziz Airport’s new terminals using the AB and the DE approaches. The simulated results of modeled airport terminals will be compared to each other to decipher which approach provides a more realistic set of solutions to this problem. Moreover, the comparison between simulated models and their results would allow an appreciation of the airport terminal’s design strengths and weaknesses. This would be utilized to provide valuable insight into the development of new terminals for expanding passenger flows at the King Abdulaziz Airport. Software Platform The current study will utilize AnyLogic as the software platform for performing AB and DE based modeling and simulation of passenger flows at the King Abdulaziz Airport terminals. AnyLogic is a multi-method modeling and simulation tool that can be used to perform DS, AB and DE problem solutions. AnyLogic has found great use in solving real world dynamic problems including pedestrian dynamics and traffic simulations (Makarov, Zitkov and Bakhtizin). AnyLogic comes bundled with process modeling and pedestrian libraries that are used to perform AB and DE simulations (AnyLogic). These libraries have been implemented for the current research to model and simulate two distinct AB and DE approaches to the problem at hand. Thesis Structure The current thesis is structured into various chapters corresponding to distinct phases in the research process. The first chapter serves as the introduction to the thesis and its major percepts. The second chapter will look into passenger dynamics in the real world and will compare it to simulated models to decipher the strengths and weaknesses of computer modeling and simulation. The third chapter will examine the characteristics of the airport terminals at King Abdulaziz Airport and will also provide for traits of passenger traffic flow inside these terminals. The fourth chapter will decipher meaningful methods and techniques to model and simulate passenger flow in the airport terminals by utilizing already available theoretical frameworks. The sixth chapter will develop implementable AB and DE approaches for simulation while noting its limitations. The seventh chapter will look into simulation results and analysis for the AB and DE approaches. The eighth chapter will serve as the discussion and conclusion where learning from the simulations will be explored and its limitations will be listed. Additionally, this chapter will serve to provide practical advice for the King Abdulaziz Airport and its expanding passenger flows to avoid problems for future expansion. Works Cited adpi. King Abdulaziz International Airport: Passenger Terminal Building, planning and design. 2014. 29 August 2014. . AnyLogic. Online Help. 2014. 31 August 2014. . Grimm, Volker and Steven F. Railsback. Individual-based Modeling and Ecology. Princeton: Princeton University Press, 2005. International Finance Corporation. "Saudi Arabia: Hajj Airport Terminal." Pamphlet. 2013. Document. King Abdulaziz International Airport. The New KAIA Project. 2014. 29 August 2014. . Makarov, V. L., V. A. Zitkov and A. R. Bakhtizin. "An agent-based model of Moscow traffic jams." Agent Based Spatial Simulation Workshop. Paris, France, 2008. Document. Matloff, Norm. "Introduction to Discrete Event Simulation and the SimPy Language." 2013. University of California at Davis. Document. 31 August 2014. . MIT. MIT System Dynamics in Education Project. 2014. 30 August 2014. . Regmi, Uttam Kumar. "Current Developments and Future Trends in Airport Ownership and Governance." Lecture. 2013. Presentation. Robinson, Stewart. Simulation – The practice of model development and use. New York: Wiley, 2004. Santner, Thomas J., Brian J. Williams and William I. Notz. The design and analysis of computer experiments. New York: Springer Verlag, 2003. Strogatz, Steven. "The End of Insight." Brockman, John. What is your dangerous idea? London: United Kingdom: Harper Collins, 2007. Read More