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

Yıl 2021, Cilt 11, Sayı 2, 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

Öz

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.

Anahtar Kelimeler

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

Öz

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.

Anahtar Kelimeler

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

Kaynakça

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