METRO LINE ON ACCESS TO ISTANBUL AIRPORT AND SIMULATION STUDY OF THE COVID-19 EFFECT

Abstract

Purpose- It has increased the demand for air transport in the medium and long distance for about two and a half times in Turkey, as in all the world, over the last decade. This increase is for the city of Istanbul in which hosting such a rate of 50% of air traffic in Turkey has brought the need for a new airport. The first phase of Istanbul Airport (IST-LTFM), that is planned to meet the increasing air transport demand in Istanbul and to increase the existing passenger and cargo carrying capacity, was completed in October 2018. Transportation to Istanbul Airport, which is located further away from the places where the settlement is dense, has gained importance due to its location. Since currently only highway transportation is available, it is planned to provide transportation to the airport by rail and seaways. In the first part of the research, the literature integration with other transportation modes, airport integration and airport access options are viewed. In this context, the information of integration between upcoming rail systems and İstanbul Airport have been obtained from secondary data sources. Methodology- In the second part of the study, the estimated number of passengers at Istanbul Airport in 2021 and the effects of the COVID-19 crisis on the forecasts have been evaluated. In the practice part of the research, through a computer-aided simulation program, the rate of GHYMETRO project's response to the estimated passenger demand in 2021 was investigated in 3 different scenarios. Findings- It is foreseen that the GHYMETRO project, which will be carried out according to the data obtained as a result of simulation analysis under effective capacity conditions (with 95% and 100% occupancy rate), can meet 70% of the total passenger demand at Istanbul Airport in the 1st Scenario. In the scenario 2, which is assumed that the COVID-19 crisis continues, it is observed that there will be 99% residual capacity in the pessimistic situation, and 72% residual capacity in optimistic situation. Finally, it is predicted that there will be 43% residual capacity in the pessimistic situation and 14% residual capacity in optimistic situation in Scenario 3, where the normalization process is evaluated after the COVID-19 crisis. Conclusion- Based on these analyses, it can be concluded that COVID-19 crises stroke almost all aviation activities and its related sectors severely so that up-to-date projects should be taken place to carry on their operations.

Keywords

• Istanbul Airport
• metro capacity
• COVID-19 crisis
• air transportation
• simulation

References

1. Akar, G. (2013). Ground access to airports, case study: Port Columbus International Airport. Journal of Air Transport Management, 25-31.
2. Barreira, A. (2012). Dissertation to obtain the Master of Science Degree in Civil Engineering: Technical University of Lisbon.
3. Chang, Y.-C. (2013). Factors affecting airport access mode choice for elderly air passengers. Transportation Research Part E, 105-112.
4. DHMİ. (2020). 2020 NİSAN, MAYIS AYI YOLCU TRAFİĞİ. ANKARA: DHMİ.
5. EUROCONTROL. (2005). Potential airport intermodality development, CARE II: MODAIR Measure and development of intermodality at airport, version 1.1. BRUSSEL: EUROCONTROL.
6. European Commission. (2011). Roadmap to a Single Euro pean Transport Area e Towards a competitive and resource efficient transport system. COM (2011) 144 final.
7. Givoni, M., & Banister, D. (2007). Role of the Railways in the Future of Air Transport. Transportation Planning and Technology, 95-112.
8. Givoni, M., & Chen, X. (2017). Airline and railway disintegration in China: the case of Shanghai Hongqiao Integrated Transport Hub. The International Journal of Transportation Research, 202-214.

9. Gokasar, İ., & Gunay, G. (2016). Mode choice behavior modeling of ground access to airports: A case study in Istanbul, Turkey. Journal of Air Transport Management, 1-7.
10. Gudmundsson, S. V., Cattaneo, M., & Redondi, R. (2020). Forecasting recovery time in air transport markets in the presence of large economic shocks: COVID-19. France: Toulouse Business School.
11. Hafner, F. B. (2019). Simulation Options for Airport Planning. Washington: National Academy of Sciences.
12. Jiang, Y., Timmermans, H., Chen, C., Sun, J., & Yao, B. (2019). Determinants of air-rail integration service of Shijiazhuang airport, China: analysis of historical data and stated preferences. Transportmetrica B: Transport Dynamics, 1572-1587.
13. Koster, P., Verhoef, P. E., & Kroes, E. (2010). Travel Time Variability and Airport Accessibility. Amsterdam: Paper No. TI 2010-061/3,.
14. Landau, S., Weisbrod, G., Gosling, G., Williges, C., Pumphrey, M., & Fowler, M. (2015). Passenger Value of Time, Benefit-Cost Analysis and Airport Capital Investment Decisions. Washington: National Academy of Sciences.
15. Mahmassani, H. S., Chebli, H., Slaughter, K., & Ludders, J. F. (2002). Assessment of Intermodal Strategies for Airport Access. Austin: Research Project 0-1849.
16. Martin, S. C. (2009). Passenger air service development techniques (No. Project 03-08).
17. Obermair, M., & Glock, B. (2014). Agent-based Simulation of the Railway Connection from and to the Vienna International Airport . Simulation Notes Europe, 123-126.
18. TRKC. (2010). Air Transport – Thematic Research Summary. Transport Research Knowledge Centre.
19. Zografos, K. G., Madas, M. A., & Salouras, Y. (2013). A decision support system for total airport operations management and planning. Journal of Advanced Transportation, 47(2), 170-189.