A Two-Door Airplane Boarding Approach When Using Apron Buses
Abstract
:1. Introduction
2. Delay Times and Boarding Methods
2.1. Air Transportation Delay and its Causes in European Airports
2.2. Boarding Methods
3. Agent-Based Modeling in NetLogo
3.1. Methodology and Model’s Parameters
3.2. Modeling the Actual Boarding Process
3.3. Modeling the Proposed Approach
4. Data Analysis and Discussions
- Case 1: all the passengers are travelling without hand luggage;
- Case 2-1: only half of the passengers are travelling with hand luggage;
- Case 2-2: only half of the passengers are travelling with hand luggage and they need time to store it in the overhead compartment;
- Case 3-1: all the passengers are travelling with hand luggage;
- Case 3-2: all the passengers are travelling with hand luggage and they need time to store it in the overhead compartment.
4.1. Data Analysis in Terms of Interferences
4.2. Data Analysis in Terms of Boarding Time
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
Appendix A. Simulation of the proposed boarding method
References
- Salzburg Airport Press. First Electric Airport Bus in Salzburg 2018; Salzburg Airport Press: Salzburg, Austria, 2018. [Google Scholar]
- Schultz, M. Implementation and application of a stochastic aircraft boarding model. Transp. Res. Part C Emerg. Technol. 2018, 90, 334–349. [Google Scholar] [CrossRef]
- Eurocontrol. All-Causes Delay and Cancellations to Air Transport in Europe-2017; Eurocontrol: Brussels, Belgium, 2018. [Google Scholar]
- Cook, A.; Tanner, G. European Airline Delay Cost Reference Values 2015; Eurocontrol: Brussels, Belgium, 2015. [Google Scholar]
- Steffen, J.H. A statistical mechanics model for free-for-all airplane passenger boarding. Am. J. Phys. 2008, 76, 1114–1119. [Google Scholar] [CrossRef] [Green Version]
- Bachmat, E.; Berend, D.; Sapir, L.; Skiena, S.; Stolyarov, N. Analysis of Airplane Boarding Times. Oper. Res. 2009, 57, 499–513. [Google Scholar] [CrossRef] [Green Version]
- Bidanda, R.; Winakor, J.; Geng, Z.; Vidic, N. A Review of Optimization Models for Boarding a Commercial Airplane. In Proceedings of the 24th International Conference on Production Research, Poznan, Poland, 30 July–3 August 2017; pp. 1–6. [Google Scholar]
- Kierzkowski, A.; Kisiel, T. The Human Factor in the Passenger Boarding Process at the Airport. Procedia Eng. 2017, 187, 348–355. [Google Scholar] [CrossRef]
- Delcea, C.; Cotfas, L.-A.; Paun, R. Agent-Based Evaluation of the Airplane Boarding Strategies’ Efficiency and Sustainability. Sustainability 2018, 10, 1879. [Google Scholar] [CrossRef]
- Milne, R.J.; Kelly, A.R. A new method for boarding passengers onto an airplane. J. Air Transp. Manag. 2014, 34, 93–100. [Google Scholar] [CrossRef]
- Milne, R.J.; Salari, M. Optimization of assigning passengers to seats on airplanes based on their carry-on luggage. J. Air Transp. Manag. 2016, 54, 104–110. [Google Scholar] [CrossRef]
- Milne, R.; Salari, M.; Kattan, L. Robust Optimization of Airplane Passenger Seating Assignments. Aerospace 2018, 5, 80. [Google Scholar] [CrossRef]
- Steffen, J.H. Optimal boarding method for airline passengers. J. Air Transp. Manag. 2008, 14, 146–150. [Google Scholar] [CrossRef] [Green Version]
- Steffen, J.H.; Hotchkiss, J. Experimental test of airplane boarding methods. J. Air Transp. Manag. 2012, 18, 64–67. [Google Scholar] [CrossRef] [Green Version]
- Ferrari, P.; Nagel, K. Robustness of Efficient Passenger Boarding Strategies for Airplanes. Transp. Res. Rec. J. Transp. Res. Board 2005, 1915, 44–54. [Google Scholar] [CrossRef]
- Soolaki, M.; Mahdavi, I.; Mahdavi-Amiri, N.; Hassanzadeh, R.; Aghajani, A. A new linear programming approach and genetic algorithm for solving airline boarding problem. Appl. Math. Model. 2012, 36, 4060–4072. [Google Scholar] [CrossRef]
- Hutter, L.; Jaehn, F.; Neumann, S. Influencing Factors on Airplane Boarding Times. Omega 2018. [Google Scholar] [CrossRef]
- Qiang, S.-J.; Jia, B.; Xie, D.-F.; Gao, Z.-Y. Reducing airplane boarding time by accounting for passengers’ individual properties: A simulation based on cellular automaton. J. Air Transp. Manag. 2014, 40, 42–47. [Google Scholar] [CrossRef]
- Tang, T.-Q.; Yang, S.-P.; Ou, H.; Chen, L.; Huang, H.-J. An aircraft boarding model with the group behavior and the quantity of luggage. Transp. Res. Part C Emerg. Technol. 2018, 93, 115–127. [Google Scholar] [CrossRef]
- Van Landeghem, H.; Beuselinck, A. Reducing passenger boarding time in airplanes: A simulation based approach. Eur. J. Oper. Res. 2002, 142, 294–308. [Google Scholar] [CrossRef]
- Van den Briel, M.H.L.; Villalobos, J.R.; Hogg, G.L.; Lindemann, T.; Mulé, A.V. America West Airlines Develops Efficient Boarding Strategies. Interfaces 2005, 35, 191–201. [Google Scholar] [CrossRef]
- Notomista, G.; Selvaggio, M.; Sbrizzi, F.; Di Maio, G.; Grazioso, S.; Botsch, M. A fast airplane boarding strategy using online seat assignment based on passenger classification. J. Air Transp. Manag. 2016, 53, 140–149. [Google Scholar] [CrossRef]
- Nyquist, D.C.; McFadden, K.L. A study of the airline boarding problem. J. Air Transp. Manag. 2008, 14, 197–204. [Google Scholar] [CrossRef]
- Ren, X.; Xu, X. Experimental analyses of airplane boarding based on interference classification. J. Air Transp. Manag. 2018, 71, 55–63. [Google Scholar] [CrossRef]
- Jafer, S.; Mi, W. Comparative Study of Aircraft Boarding Strategies Using Cellular Discrete Event Simulation. Aerospace 2017, 4, 57. [Google Scholar] [CrossRef]
- Airplane Turn Time. Available online: http://www.boeing.com/commercial/aeromagazine/aero_01/textonly/t01txt.html (accessed on 30 May 2018).
- Schultz, M. Fast Aircraft Turnaround Enabled by Reliable Passenger Boarding. Aerospace 2018, 5, 8. [Google Scholar] [CrossRef]
- Schultz, M. A metric for the real-time evaluation of the aircraft boarding progress. Transp. Res. Part C Emerg. Technol. 2018, 86, 467–487. [Google Scholar] [CrossRef]
- Schultz, M. Dynamic change of aircraft seat condition for fast boarding. Transp. Res. Part C Emerg. Technol. 2017, 85, 131–147. [Google Scholar] [CrossRef]
- Bazargan, M. A linear programming approach for aircraft boarding strategy. Eur. J. Oper. Res. 2007, 183, 394–411. [Google Scholar] [CrossRef]
- Schultz, M. The Seat Interference Potential as an Indicator for the Aircraft Boarding Progress; SAE International: Warrendale, PA, USA, 2017. [Google Scholar]
- Steiner, A.; Philipp, M. Speeding up the airplane boarding process by using pre-boarding areas. In Proceedings of the 9th Swiss Transport Research Conference, Ascona, Switzerland, 9–11 September 2009. [Google Scholar]
- Tang, T.-Q.; Wu, Y.-H.; Huang, H.-J.; Caccetta, L. An aircraft boarding model accounting for passengers’ individual properties. Transp. Res. Part C Emerg. Technol. 2012, 22, 1–16. [Google Scholar] [CrossRef]
- Jaehn, F.; Neumann, S. Airplane boarding. Eur. J. Oper. Res. 2015, 244, 339–359. [Google Scholar] [CrossRef]
- Schultz, M.; Kunze, T.; Fricke, H. Boarding on the critical path of the turnaround. In Proceedings of the Tenth USA/Europe Air Traffic Management Research and Development Seminar, Chicago, IL, USA, 10–13 June 2013; pp. 1–10. [Google Scholar]
- Schultz, M.; Schulz, C.; Fricke, H. Efficiency of Aircraft Boarding Procedures. In Proceedings of the 3rd International Conference on Research in Airport Transportation, Fairfax, VA, USA, 1–4 June 2008; Volume 371–391. [Google Scholar]
- Gao, M.; Zhou, L.; Chen, Y. An Alternative Approach for High Speed Railway Carrying Capacity Calculation Based on Multiagent Simulation. Discret. Dyn. Nat. Soc. 2016, 2016, e4278073. [Google Scholar] [CrossRef]
- Riaz, F.; Jabbar, S.; Sajid, M.; Ahmad, M.; Naseer, K.; Ali, N. A collision avoidance scheme for autonomous vehicles inspired by human social norms. Comput. Electr. Eng. 2018. [Google Scholar] [CrossRef]
- Dossetti, V.; Bouzat, S.; Kuperman, M.N. Behavioral effects in room evacuation models. Phys. A Stat. Mech. Appl. 2017, 479, 193–202. [Google Scholar] [CrossRef]
- Delcea, C.; Cotfas, L.-A.; Paun, R. Agent-Based Optimization of the Emergency Exits and Desks Placement in Classrooms. In Computational Collective Intelligence; Nguyen, N.T., Pimenidis, E., Khan, Z., Trawiński, B., Eds.; Springer International Publishing: Cham, Switzerland, 2018; Volume 11055, pp. 340–348. ISBN 978-3-319-98442-1. [Google Scholar]
- Prachai, S. The Design of Diabetes Simulation System using Multi-Agent. Procedia Soc. Behav. Sci. 2012, 40, 146–151. [Google Scholar] [CrossRef]
- Pardo, M.; Coronado, W.F. Agent-based Modeling and Simulation to Adoption Process of Information Technologies in Health Systems. IEEE Latin Am. Trans. 2016, 14, 3358–3363. [Google Scholar] [CrossRef]
- Castilla-Rho, J.C.; Mariethoz, G.; Rojas, R.; Andersen, M.S.; Kelly, B.F.J. An agent-based platform for simulating complex human–aquifer interactions in managed groundwater systems. Environ. Model. Softw. 2015, 73, 305–323. [Google Scholar] [CrossRef]
- West, T.A.P.; Grogan, K.A.; Swisher, M.E.; Caviglia-Harris, J.L.; Sills, E.; Harris, D.; Roberts, D.; Putz, F.E. A hybrid optimization-agent-based model of REDD+ payments to households on an old deforestation frontier in the Brazilian Amazon. Environ. Model. Softw. 2018, 100, 159–174. [Google Scholar] [CrossRef]
- Delcea, C.; Bradea, I.A.; Cotfas, L.A.; Scarlat, E. Opinion influence in online social media environments—U grey system theory and agent-based modeling approach. In Proceedings of the 2017 International Conference on Grey Systems and Intelligent Services (GSIS), Stockholm, Sweden, 8–11 August 2017; pp. 349–355. [Google Scholar]
- Delcea, C.; Cotfas, L.-A.; Paun, R. Airplane Boarding Strategies Using Agent-Based Modeling and Grey Analysis. In Computational Collective Intelligence; Nguyen, N.T., Pimenidis, E., Khan, Z., Trawiński, B., Eds.; Springer International Publishing: Cham, Switzerland, 2018; Volume 11055, pp. 329–339. ISBN 978-3-319-98442-1. [Google Scholar]
- Schultz, M. Field Trial Measurements to Validate a Stochastic Aircraft Boarding Model. Aerospace 2018, 5, 27. [Google Scholar] [CrossRef]
- Delcea, C.; Bradea, I.A. Economic Cybernetics: An Equation-Based Modeling and Agent-Based Modeling Approach; Editura Universitara: București, Romania, 2017; ISBN 978-606-28-0629-3. [Google Scholar]
- Wilensky, U.; Rand, W. An introduction to Agent-Based Modeling: Modeling Natural, Social, and Engineered Complex Systems with NetLogo; The MIT Press: Cambridge, MA, USA, 2015; ISBN 978-0-262-73189-8. [Google Scholar]
- Iyigunlu, S.; Fookes, C.; Yarlagadda, P. Agent-based Modelling of Aircraft Boarding Methods. In Proceedings of the 4th International Conference on Simulation and Modeling Methodologies, Technologies and Applications; SCITEPRESS—Science and Technology Publications: Vienna, Austria, 2014; pp. 148–154. [Google Scholar]
Classification | Boarding Method | Main Idea |
---|---|---|
By group | Outside-in (WilMA) * | The passengers are divided into three groups depending on their seat position: near the window, middle, or aisle. The first called-in group is formed by the passengers with seats near the window, then middle, and last aisle. |
Reverse pyramid | The groups board diagonally, starting with some of the seats located near the window, then, the remaining part of the seats near the window and some of the seats in the middle, and so on, ending with the some of the seats near the aisle. | |
Back-to-front | The passengers board in groups starting from the rear of the airplane and move forward about one fifth of the number of seat rows at a time. | |
Rotating zone | The boarding starts with a group located in the rear, continues with a group in the front, then back in the rear again, and back to the front, while the group formed by the seats located in the middle of the airplane is boarded last. | |
Modified optimal method | The even seat rows from one side of the aisle are boarded in the first group, followed by the even seat rows located on the other side of the aisle, then, the un-even rows of one side and last the un-even rows on the other side, making a total of four boarding groups. | |
Non-traditional method | First, a few seat rows located in the back-middle side of the airplane are boarded, followed by the rows in the middle, the rows in the front and last the rows in the rear of the airplane. Even in this case, four boarding groups are used. |
Issue | Resulted from: | Type 1 | Type 2 | Type 3 | Type 4 |
---|---|---|---|---|---|
No. of seat interference situations | Random with assigned seats | 18.4 | 10.6 | 10.8 | 27.6 |
Proposed approach | 18.6 | 9.3 | 11.6 | 32.8 |
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Delcea, C.; Cotfas, L.-A.; Chiriță, N.; Nica, I. A Two-Door Airplane Boarding Approach When Using Apron Buses. Sustainability 2018, 10, 3619. https://doi.org/10.3390/su10103619
Delcea C, Cotfas L-A, Chiriță N, Nica I. A Two-Door Airplane Boarding Approach When Using Apron Buses. Sustainability. 2018; 10(10):3619. https://doi.org/10.3390/su10103619
Chicago/Turabian StyleDelcea, Camelia, Liviu-Adrian Cotfas, Nora Chiriță, and Ionuț Nica. 2018. "A Two-Door Airplane Boarding Approach When Using Apron Buses" Sustainability 10, no. 10: 3619. https://doi.org/10.3390/su10103619