Analysis of car park etudes with different statistical methods and modeling with GIS: Erzincan province case

Year 2021, , 497 - 509, 15.04.2021

Yusuf Mazlum , Halim Ferit Bayata , Fatih İrfan Baş , Muhammed Ali Çolak , Osman Ünsal Bayrak

https://doi.org/10.17714/gumusfenbil.685894

Abstract

Rapidly changing lifestyles, rising expectations, and increased private vehicle ownership have caused increases in the number of urban trips. All these changes that have appeared in time have made the parking requirement more important every day. Parking surveys have been required to determine what actions to be taken leadingly during the location selection and building processes of the parking areas to be built. The failure on planning parking areas correctly reveals environmental and economic problems as well as social problems. In this study, parking surveys were carried out primarily in order to determine location, types and capacities of existing car parks. The capacity and locations of the new parking areas have been determined considering five-year traffic increases. The points where parking needs were most needed were determined counting the vehicles parked at 44 separate on-road parking areas in the city center of Erzincan, where parking fees are charged by the municipality. In determined parking areas, statistical analyses were performed with spatial analysis outputs, artificial neural networks and time series analysis methods counting the vehicles parked regularly during daylight hours for one year. Solutions were offered to reduce parking load in traffic identifying new correctly located car parking areas in Erzincan city center. In the light of the analysis results, the location and capacities of the new parking areas suggested to be built identifying 6 different points in the city center were determined. In conclusion, an additional 1420-vehicle parking capacity in suggested new parking spaces was proposed as a solution-oriented approach for the parking problem in the city center.

Keywords

Artificial neural networks, Location selection, Parking survey, Spatial analysis, Time series analysis

Otopark etütlerinin farklı istatistiksel yöntemler ile analizi ve CBS ile modellenmesi: Erzincan ili örneği

Abstract

Hızla değişen yaşam tarzları, yükselen beklentiler, özel araç sahipliğinin artması, kentsel yolculuk sayılarında artışlara neden olmaktadır. Zaman içinde meydana gelen tüm bu değişiklikler otopark gereksinimini her geçen gün daha da önemli kılmaktadır. Yapılacak olan otopark alanlarının konum seçimi ve kurulum süreçleri içerisinde başlangıç olarak yapılması gerekenlerin neler olduğunu belirlemek için otopark etütlerinin yapılması gerekmektedir. Otopark alanlarının doğru planlanmaması, çevresel ve ekonomik sorunların yanında sosyal problemleri de ortaya çıkarmaktadır. Bu çalışmada öncelikle mevcut otoparkların konum, tür ve kapasitelerinin belirlenmesi amacıyla otopark etütleri yapılmıştır. Beş yıllık trafik artışları da dikkate alınarak yeni otopark alanlarının kapasite ve konumları belirlenmiştir. Erzincan ili şehir merkezinde bulunan ve belediye tarafından park ücreti alınan 44 ayrı yol üzeri park alanı noktasında park eden araçların sayımları yapılarak otopark ihtiyacının en çok olduğu noktalar tespit edilmiştir. Belirlenen park alanlarında, bir yıl boyunca düzenli olarak gündüz saatlerinde park eden araç sayımları yapılarak mekânsal analiz çıktıları, yapay sinir ağları ve zaman serileri analizi yöntemleri ile istatiksel analizleri yapılmıştır. Erzincan kent merkezinde bulunan doğru konumlandırılmış yeni otopark alanları belirlenerek trafikteki otopark yükünü azaltmaya yönelik çözüm önerileri sunulmuştur. Ortaya çıkan analiz sonuçları ışığında il merkezinde 6 ayrı nokta belirlenerek yapılması önerilen yeni otopark alanlarının konum ve kapasiteleri belirlenmiştir. Sonuç olarak önerilen yeni park alanlarındaki 1420 araçlık ek otopark kapasitesi il merkezindeki otopark problemine çözüm odaklı bir yaklaşım önerilmiştir.

Keywords

Yapay sinir ağları, Konum seçimi, Otopark etüdü, Mekânsal analiz, Zaman serileri analizi

References

• Ahmad, S., Khan, I. H. and Parida, B. (2001). Performance of stochastic approaches for forecasting river water quality. Water Research,35(18), 4261–4266. https://doi.org/10.1016/s0043-1354(01)00167-1
• Alkheder, S. A., Rajab, M. M. A. and Alzoubi, K. (2016). Parking problems in Abu Dhabi, UAE toward an intelligent parking management system. Alexandria Engineering Journal, 55(3), 2679–2687. https://doi.org/10.1016/j.aej.2016.06.012
• Aslan, Ş., (1998), Transformation of informal sectors in terms of urban sociology: Parking sector in Istanbul, Master Thesis, Mimar Sinan University Institute of Social Sciences, Istanbul.
• Barhani, E., (2007), Parking management strategies for sustainable transportation: case study for İstanbul, Master Thesis, Boğaziçi University Institute of Social Sciences, Istanbul.
• Cadenas, E. and Rivera, W. (2010). Wind speed forecasting in three different regions of Mexico, using a hybrid ARIMA–ANN model. Renewable Energy, 35(12), 2732–2738. https://doi.org/10.1016 / j.renene.2010.04.022
• Chattopadhyay, S. and Chattopadhyay, G. (2010). Univariate modelling of summer-monsoon rainfall time series: Comparison between ARIMA and ARNN. Comptes Rendus Geoscience, 342(2), 100–107. https://doi.org/10.1016/j.crte.2009.10.016
• Çıkman, G., (2003), A research for the request of parking spaces in cities and design options, Master Thesis, Dokuz Eylül University Institute of Science, İzmir.
• Çiçek, C. (2015). Investigating the applicability of new technologies used in tparking lots in Turkey. Master Thesis, Eskişehir Osmangazi University Institute of Science, Eskişehir.
• Dey, S. K., Shamim, R. M. R., Islam, M. A. and Rahman, M. M. (2019). ParkEasy: An embedded model to mitigate car parking problems using iot technology. In 2019 1st International Conference on Advances in Science, Engineering and Robotics Technology (ICASERT) (Vol. 2019, pp. 1–7). https://doi.org/10.31590/ejosat.792594
• Durduran, Ş.S. Gümüş, G.G., Bozdağ, A. and Beyhan, C.H. (2018). Route optimization over pedestrian roads using geographic information systems, Ömer Halis Demir University Journal of Engineering Sciences, 7, (1), 180- 189. https://doi.org/10.28948/ngumuh.386473
• Gökdağ M. and Yarbaşı S., 10.10.2018., A research on parking lots as one of the transportation problems and an Erzurum case, Access address http://www.e-kutuphane.imo.org.tr.
• Green, S., (2021, January 22). Time series analysis of stock prices using the box-Jenkins approach. https://digitalcommons.georgiasouthern.edu/cgi/viewcontent.cgi?article=1668&context=etd
• Güngör, E.K., (2006), Parking problem in Konya city center and recommendations, Master Thesis, Selcuk University Institute of Science, Konya.
• Haldenbilen, S., Murat, Y., Baykan, N. and Meriç, N. (1999). Parking problem in cities: a Denizli case, Journal of Engineering Sciences, 5: 2-3: 1099-1108.
• Hanchette, L. (2014). Geographic İnformation Systems, 399–427.
• İskender, E., (2010), Design and application examples of real-time on-site research system for parking lot survey methodology, Master Thesis, Bahçeşehir University Institute of Science, Istanbul.
• Kaplan, H. and Yıldız, D., (2002), Investigating the relationship between car park areas and pedestrian areas in Ankara city center in terms of road and traffic safety in Kızılay case, Master Thesis, Gazi University Institute of Science, Ankara.
• Karasar, İ. (1994), Scientific Research Methods (87), Istanbul, Nobel Publications.
• Kargı, B., (2013), Minimum wage in Turkey and time-series analysis on growth (2005-2012), Journal of Labor and Society, 37, 183-210.
• Özbuğday, T. I., (2009), Determining the need for parking in Antakya city development plans and examining in terms of landscape architecture, Master Thesis, Mustafa Kemal University Institute of Science, Hatay.
• Özdemir, İ., (2006), Park and go facilities and Harem parking lot case, Master Thesis, Yıldız Technical University Institute of Science, Istanbul.
• Özel, S., (1996), Parking problem in Istanbul: Şişli-Beşiktaş cases, Master Thesis, Istanbul Technical University Institute of Science, Istanbul.
• Özen, M., (2014), Parking lot planning and management in small cities, an Artvin case, Master Thesis, Yıldız Technical University Institute of Science and Technology, Istanbul.
• Remoaldo, P. C. A., Ribeiro, V., Lopes, H. S. and Silva, S. C. G. (2018). Geographic Information Systems (pp. 3460–3472).
• Sandal, E., K. and M., Traş, (2009), Transportation problems in Kahramanmaraş and the public's view on transportation system and problems, Eastern Geography Journal, 14, 21, 137-157.
• Strasser, M., Mauser, D. and Albayrak, S. (2016). Reducing traffic problems integrating smart parking solutions into an interconnected ecosystem. 2016 IEEE Symposium with Computer and communications (ISCC) (pp. 32-37).
• Varol, T., Özel, H. B. and Macaroğlu, K. (2010). The possibilities of using network analysis in forest fires (Yenihan forest management directorate case study). 2010, III. National Black Sea Forestry Congress, Artvin.
• Yalınız, P. and Bilgiç, Ş., (2006), Evaluation of park-and-ride application in Eskişehir city center within the context of sustainable transportation, 7th Transportation Congress, Yıldız Technical University, Istanbul.
• Yomralıoğlu, T., (2000), Geographic Information Systems Basic Concepts and Applications, Istanbul, Academy Publishing.
• Wang, H. R., Wang, C., Lin, X. and Kang, J. (2014). An improved ARIMA model for precipitation simulations. Nonlinear Processes in Geophysics, 21(6), 1159–1168. https://doi.org/10.5194 / npg-21-1159-2014
• Wang, D., Han, X. and Xing, G. (2016). Research on fundamental solutions to curb parking problems in city. International Conference on Green Intelligent Transportation System and Safety, 439–445.