بررسی نقش پارامترهای مکانی در تعیین ظرفیت راه آهن در GIS (مطالعه موردی: ایران)
محورهای موضوعی : کاربرد GIS&RS در برنامه ریزیبهرام مرادی سلوشی 1 , سمیرا بلوری 2 , محمدصادق زنگنه 3 , اکرم کرامت 4
1 - دکترای سنجش از دور و سیستم اطلاعات جغرافیایی، راه آهن جمهوری اسلامی ایران، ایران.
2 - دکترای سنجش از دور و سیستم اطلاعات جغرافیایی، راه آهن جمهوری اسلامی ایران، ایران
3 - گروه سنجش از دور و سیستم اطلاعات جغرافیایی، واحد دزفول، دانشگاه آزاد اسلامی، دزفول، ایران.
4 - گروه سنجش از دور و سیستم اطلاعات جغرافیایی، واحد دزفول،دانشگاه آزاد اسلامی،دزفول، ایران.
کلید واژه: راه آهن, پارامترهای مکانی, GIS.,
چکیده مقاله :
حمل و نقل ریلی به عنوان یک صنعت ایدهآل در جهان توسعه یافته در نظر گرفته میشود. راهآهن در بسیاری از کشورها همچنان در تلاش است تا از نظر تجاری کارآمدتر و با دوام باشد. این روش حمل و نقل ایمن، کارآمد و سازگار با محیط زیست در نظر گرفته می شود. این صنعت با ارائه خدمات قابل اعتماد و مقرون به صرفه باعث رشد اقتصادی میشود و نقش مهمی در زندگی انسان ایفا میکند. این تحقیق از طریق رگرسیون خطی ظرفیت راهآهن را در یک مطالعه موردی برای مسیرهای منتخب تعیین و بلوکهای بحرانی را مشخص میکند تا تأثیر پارامترهای مکانی در تعیین ظرفیت شبکه ریلی مورد بحث قرار گیرد. از طریق دادههای موجود مربوط به سال 2017، پیشبینی ظرفیت سال 2018 در محیط GIS انجام شد و سپس از طریق پارامترهای آماری RMSE، R^2 و MAE صحت پیشبینی ظرفیت برای دادههای موجود سال 2018 انجام شد. نتایج نشان داد که ظرفیت استفاده از مسیرهای انتخابی برای قطارهای باری 82 درصد، قطارهای مسافری در مسیر رفت 56 درصد، در مسیر برگشت 62 درصد و در مسیرهای ترکیبی 79 درصد بوده است. همچنین پیشبینی دقت قطارهای باری 35 درصد بهتر از قطارهای مسافری بود. در مسیر مسافری، قطارهای مسافری دقت بیشتری داشتند (تقریباً 45 درصد). به همین ترتیب در مسیر باری ظرفیت قطارهای باری از دقت بالاتری (نزدیک به 45 درصد) برخوردار بود.
Railway transport is considered a mature industry in the developed world. Railways in many countries are still struggling to become more commercially efficient and sustainable. This method of transportation is considered safe, efficient and environmentally friendly. By providing reliable and affordable services, this industry causes economic growth and plays an important role in human life. This research, through the linear regression, determines the capacity of the railway in a case study in Iran for the selected routes and pinpoints the critical blocks to discuss the effect of spatial parameters in determining the capacity of the railway network. Through the existing 2017-related data, the capacity forecast of 2018 was done in GIS environment, and then via the RMSE, R^2, and MAE statistical parameters, the accuracy of the capacity forecast for the extant data of 2018 was performed. The results showed that the capacity of utilizing the selected routes was 82% for cargo trains, 56% for passenger trains on the road, 62% on the way back and 79% on the combined routes. Also, the accuracy prediction of cargo trains was 35% better than that of passenger trains. In the passenger route, the passenger trains were more accurate (approximately 45%). Similarly, in the cargo route, the capacity of cargo trains was of higher accuracy (nearly 45%).
-Blainey, S. P., & Preston, J. M. (2013). A GIS-based appraisal framework for new local railway stations and services. Transport Policy, 25, 41-51.
-Bolouri, S., Vafaeinejad, A., Alesheikh, A. A., & Aghamohammadi, H. (2018). The ordered capacitated multi-objective location-allocation problem for fire stations using spatial optimization. ISPRS International Journal of Geo-Information, 7(2), 44.
-Bolouri, S., Vafaeinejad, A., Alesheikh, A., & Aghamohammadi, H. (2020). Minimizing response time to accidents in big cities: a two ranked level model for allocating fire stations. Arabian Journal of Geosciences, 13(16), 758.
-Burdett, R. L. (2016). Optimisation models for expanding a railway's theoretical capacity. European Journal of Operational Research, 251(3), 783-797.
-Burdett, R. L., & Kozan, E. (2006). Techniques for absolute capacity determination in railways. Transportation Research Part B: Methodological, 40(8), 616-632.
-Do, W., Rouhani, O. M., Geddes, R. R., & Beheshtian, A. (2021). Social impact analysis of various road capacity expansion options: a case of managed highway lanes. Journal of transportation engineering, Part A: Systems, 147(7), 04021033.
-Dicembre, A., & Ricci, S. (2011). Railway traffic on high density urban corridors: capacity, signalling and timetable. Journal of Rail Transport Planning & Management, 1(2), 59-68.
-El-Bakry, H. M., & Awad, W. A. (2010, November). Geographic information system for railway management. In Proceedings of the 3rd WSEAS international conference on Visualization, imaging and simulation (pp. 149-163).
-Farooq, A., Xie, M., Stoilova, S., Ahmad, F., Guo, M., Williams, E. J., ... & Mahamat Issa, A. (2018). Transportation planning through GIS and multicriteria analysis: Case study of Beijing and XiongAn. Journal of Advanced Transportation, 2018.
-Feng, T., Lusby, R. M., Zhang, Y., Peng, Q., Shang, P., & Tao, S. (2023). An ADMM-based dual decomposition mechanism for integrating crew scheduling and rostering in an urban rail transit line. Transportation Research Part C: Emerging Technologies, 149, 104081.
-Goverde, R. M., Corman, F., & D’Ariano, A. (2013). Railway line capacity consumption of different railway signalling systems under scheduled and disturbed conditions. Journal of rail transport planning & management, 3(3), 78-94.
-Harrod, S. (2009). Capacity factors of a mixed speed railway network. Transportation Research Part E: Logistics and Transportation Review, 45(5), 830-841.
-Jamili, A. (2018). Computation of practical capacity in single-track railway lines based on computing the minimum buffer times. Journal of Rail Transport Planning & Management, 8(2), 91-102.
-Jensen, L. W., Landex, A., Nielsen, O. A., Kroon, L. G., & Schmidt, M. (2017). Strategic assessment of capacity consumption in railway networks: Framework and model. Transportation Research Part C: Emerging Technologies, 74, 126-149.
-Kaleybar, H. J., Kojabadi, H. M., Fazel, S. S., & Foiadelli, F. (2018). An intelligent control method for capacity reduction of power flow controller in electrical railway grids. Electric Power Systems Research, 165, 157-166.
-Kotavaara, O., Antikainen, H., & Rusanen, J. (2011). Population change and accessibility by road and rail networks: GIS and statistical approach to Finland 1970–2007. Journal of Transport Geography, 19(4), 926-935.
-Landex, A. (2007, December). Capacity statement for railways. In Selected Proceedings from the Annual Transport Conference at Aalborg University (Vol. 2, No. 1).
-Landex, A., Kaas, A. H., Schittenhelm, B., & Schneider-Tilli, J. (2006). Practical use of the UIC 406 capacity leaflet by including timetable tools in the investigations. WIT Transactions on the Built Environment, 88.
-Landex, A., Schittenhelm, B., Kaas, A. H., & Schneider-Tilli, J. (2008, August). Capacity measurement with the UIC 406 capacity method. In Proceedings of the 11th International Conference on Computers in Railways (p. 55).
-Li, F., Gao, Z., Wang, D. Z., Liu, R., Tang, T., Wu, J., & Yang, L. (2017). A subjective capacity evaluation model for single-track railway system with δ-balanced traffic and λ-tolerance level. Transportation Research Part B: Methodological, 105, 43-66.
-Lindfeldt, A. (2015). Railway capacity analysis: Methods for simulation and evaluation of timetables, delays and infrastructure (Doctoral dissertation, KTH Royal Institute of Technology).
-Mussone, L., & Calvo, R. W. (2013). An analytical approach to calculate the capacity of a railway system. European Journal of Operational Research, 228(1), 11-23.
-Odolinski, K., & Boysen, H. E. (2019). Railway line capacity utilisation and its impact on maintenance costs. Journal of Rail Transport Planning & Management, 9, 22-33.
-Riejos, F. A. O., Barrena, E., Ortiz, J. D. C., & Laporte, G. (2016). Analyzing the theoretical capacity of railway networks with a radial-backbone topology. Transportation Research Part A: Policy and Practice, 84, 83-92.
-Sameni, M. K., Landex, A., & Preston, J. (2011). Developing the UIC 406 method for capacity analysis. In 4th international seminar on railway operations research. Italy Rome.
-Sharma, B., Pellegrini, P., Rodriguez, J., & Chaudhary, N. (2023). A review of passenger-oriented railway rescheduling approaches. European Transport Research Review, 15(1), 14.
-Suyabatmaz, A. Ç., & Şahin, G. (2015). Railway crew capacity planning problem with connectivity of schedules. Transportation Research Part E: Logistics and Transportation Review, 84, 88-100.
-Yi, S. (2017). Principles of railway location and design. Academic Press.
-Zhao, L., Zhao, Y., Hu, Q., Li, H., & Stoeter, J. (2018). Evaluation of consolidation center cargo capacity and loctions for China railway express. Transportation Research Part E: Logistics and Transportation Review, 117, 58-81.
-Zheng, Y., Zhang, X., Bin, X. U., & Linli, W. A. N. G. (2011). Carrying capacity reliability of railway networks. Journal of transportation systems engineering and information technology, 11(4), 16-21.