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Yaya Yolu Ana Akslarının Belirlenmesinde Ulaşım Talebi Odaklı Çevresel Yaklaşım

Yıl 2023, Cilt: 5 Sayı: 1, 49 - 67, 01.05.2023
https://doi.org/10.53472/jenas.1248635

Öz

Yaya yolu planlaması genellikle mevcut yaya hareketlerinin yoğunlaştığı bölgelerde ele alınmakta ya da arazi kullanım çekiciliği yüksek olan tesislere erişebilmek kapsamında ele alınmaktadır. Ana akslarının belirlenmesi, yaya ağının ortaya çıkmasında temel omurganın belirlenmesi anlamına gelmektedir. Ana akslar belirlenirken, arazi kullanım çekiciliği olan unsurlara veya sadece yoğun kentsel hareket içeren merkeze odaklanmak her zaman doğru sonuç vermeyebilir. Bunun yerine, kentsel ulaşım alışkanlıklarının/taleplerinin ön plana konulması tercih edilebilir. Böylece diğer ulaşım türlerinden yaya türüne geçişler daha fazla teşvik edilebilir. Yaya akslarının, ev-iş ve ev-okul talepleri doğrultusunda belirlenmesi veya başka ulaşım türleri yerine tercih edilebilecek kadar sosyal/fiziki altyapı olanakları ile donatılması/güçlendirilmesi, ulaşım türleri arasındaki geçişleri teşvik edecektir. Belirlenen rotalardaki konfor-estetik-işlevsellik gibi özelliklerinin arttırılarak başka türlerden geçişlerin teşvik edilmesi politikası benimsenmelidir. Bu çalışmada, yaya türüne geçişlerin arttırılmasını sağlayacak ana yaya rotalarının belirlenmesi hedeflenmiştir. Bu doğrultuda ulaşım ana planı verilerinin kullanılarak rotaların belirlendiği yeni bir yaklaşım üretilmiştir. Öncelikle, kentsel erişim talebinin yüksek olduğu akslar ve mahalleler tespit edilmiştir. Yürünebilir mesafe ve ulaşım alışkanlıkları değerlendirilmiştir. Ana yaya aksları, yönler ve rotalarının belirlenmesi için türler arası geçişleri teşvik eden bir yaklaşım/model geliştirilmiştir.

Kaynakça

  • Adinarayana, B., & Mir, M. S. (2021). Modeling and application of AHP approach for development of pedestrian safety index (PSI) model for safety of pedestrian flows in urban areas of developing countries. Innovative Infrastructure Solutions, 6(3), 1-14.
  • Aultman-Hall, L., Roorda, M., & Baetz, B. W. (1997). Using GIS for evaluation of neighborhood pedestrian accessibility. Journal of urban planning and development, 123(1), 10-17.
  • Aydemir, P. K., Yılmazsoy, B. K., Akyüz, B., & Akdemir, Ç. (2018). Kentsel Ulaşımda Yaya Öncelikli Planlama/Tasarım Ve Transit Odaklı Gelişimin Metropol Kentlerdeki Deneyimi, İstanbul Örneği. Kent Akademisi, 11(4), 523-544.
  • Berg, A., & Newmark, G. L. (2020). Incorporating equity into pedestrian master plans. Transportation research record, 2674(10), 764-780.
  • Ceylan, H. & Gulhan, G., (2017). Denizli'nin Kentiçi Ulaşım Altyapısı, Ulaşımın Planlama Süreçleri ile Etkileşimi ve Geleceği. Denizli Kent Ekonomisi, Denizli Basımevi.
  • Chin, K. K., & Menon, G. (2015, June). Transport accessibility and infrastructure in Singapore–pedestrian facilities. In Proceedings of the Institution of Civil Engineers-Municipal Engineer (Vol. 168, No. 2, pp. 133-139). Thomas Telford Ltd.
  • Clifton, K., Singleton, P. A., Muhs, C. D., & Schneider, R. J. (2015). Development of a pedestrian demand estimation tool.
  • Coza, H., (2019). Denizli’de Yönetmeliklerin Nitelikli ve Özgün Konut Tasarımına Etkisi. Ege Mimarlık, Mimarlar Odası İzmir Şubesi, 2019/2-103, 39-43.
  • Desyllas, J., Duxbury, E., Ward, J., & Smith, A. (2003). Pedestrian demand modelling of large cities: an applied example from London
  • Dhanani, A., Tarkhanyan, L., & Vaughan, L. (2017). Estimating pedestrian demand for active transport evaluation and planning. Transportation research part A: policy and practice, 103, 54-69.
  • Dilip, A., ‘Complete street planning workbook’, The Institute for Transportation and Development Policy, Bundestag, (2009).
  • DUAP, 2010. Denizli Ulaşım Ana Planı. Denizli Belediyesi.
  • Gaputra, A. D., Widiastuti, I., & Estika, N. D. (2020, July). The Implementation of Transit-Oriented Development Concepts on Pedestrian Pathways in the City of Bandung. In IOP Conference Series: Earth and Environmental Science (Vol. 532, No. 1, p. 012019). IOP Publishing.
  • Gulhan, G., & Ceylan, H. (2016). Relation Between Land Use and Transportation Planning in the Scope of Smart Growth Strategies: Case Study of Denizli, Turkey. Sustainable Urbanization. IntechOpen, ISBN: 978-953-51-2652-2. Chapter 14.
  • Gültekin, B., “Kent İçi Yolların Yaya Kullanımına Yönelik Değerlendirilmesinde Çözümlemeli Bir Yaklaşım: Adana Örneği” Yüksek Lisans Tezi, Çukurova Üniversitesi Fen Bilimleri Enstitüsü, Adana, (2007).
  • Hoogendoorn, S. P., & Bovy, P. H. (2004). Pedestrian route-choice and activity scheduling theory and models. Transportation Research Part B: Methodological, 38(2), 169-190.
  • Hydén, C., ‘Walkıng’, Department of Traffıc Plannıng and Engıneerıng, Helsınkı, (1999).
  • Jabbari, M., Fonseca, F., & Ramos, R. (2018). Combining multi-criteria and space syntax analysis to assess a pedestrian network: The case of Oporto. Journal of Urban Design, 23(1), 23-41.
  • Kasemsuppakorn, P., & Karimi, H. A. (2013). A pedestrian network construction algorithm based on multiple GPS traces. Transportation Research Part C: Emerging Technologies, 26, 285-300.
  • Kim, B., & Pineau, J. (2016). Socially adaptive path planning in human environments using inverse reinforcement learning. International Journal of Social Robotics, 8(1), 51-66.
  • Larco, N., Steiner, B., Stockard, J., & West, A. (2012). Pedestrian-friendly environments and active travel for residents of multifamily housing: The role of preferences and perceptions. Environment and Behavior, 44(3), 303-333.
  • Lerman, Y., Rofè, Y., & Omer, I. (2014). Using space syntax to model pedestrian movement in urban transportation planning. Geographical Analysis, 46(4), 392-410.
  • Lilasathapornkit, T., Rey, D., Liu, W., & Saberi, M. (2022). Traffic assignment problem for footpath networks with bidirectional links. Transportation Research Part C: Emerging Technologies, 144, 103905.
  • McDonald K., Walk&roll: Memphıs regıon pedestrıan and bıcycle plan, Memphıs Urban Area Metropolıtan Plannıng Organizatıon, Florıda, (2020).
  • Mıtchell K., ‘Plannıng for walkıng’, Chartered Institution of Hıghways & Transportatıon, London, (2015).
  • Mohammad Azlan, A. I., & Naharudin, N. (2020). Measuring safety index for pedestrian path by using AHP-GIS. Built Environment Journal (BEJ), 17(3), 67-75.
  • Moore, R. L. (1953). Pedestrian choice and judgment. Journal of the Operational Research Society, 4(1), 3-10.
  • Nazir M.I., Al Razi K.M.A, Hossain, Q.S., Adhikary, S.K. (2014). Proceedings of the 2nd International Conference on Civil Engineering for Sustainable Development(ICCESD-2014), 14~16 February 2014, KUET, Khulna, Bangladesh, ISBN: 978-984-33-6373-2
  • Perotte, P., ‘Bıcycle and pedestrian master plan’, California, (2018).
  • Saunders, L. E., Green, J. M., Petticrew, M. P., Steinbach, R., & Roberts, H. (2013). What are the health benefits of active travel? A systematic review of trials and cohort studies. PloS one, 8(8), e69912.
  • Sayyadi, G., & Awasthi, A. (2013). AHP-based approach for location planning of pedestrian zones: Application in Montréal, Canada. Journal of transportation engineering, 139(2), 239-246.
  • Tal, G., & Handy, S. (2012). Measuring Non-motorized Accessibility and Connectivity in a Robust Pedestrian Network. Transportation Research Record, 2299(1), 48–56. https://doi.org/10.3141/2299-06
  • Terh, S. H., & Cao, K. (2018). GIS-MCDA based cycling paths planning: a case study in Singapore. Applied Geography, 94, 107-118.
  • Trinh, T. T., Vu, D. M., & Kimura, M. (2020, March). A pedestrian path-planning model in accordance with obstacle's danger with reinforcement learning. In Proceedings of the 2020 The 3rd International Conference on Information Science and System (pp. 115-120).
  • TÜİK, 2019. Denizli İli Nüfus Verileri. Ünal Çilek, M. (2020). Kamusal Alanlara Erişimde Optimum Yaya Güzergâhı Konforunu Belirlemeye Yönelik Kavramsal Bir Yaklaşım. Megaron,15(3):490-507.
  • Victoria Transport Institute. Pedestrian and Bicycle Planning Guide to Best Practices. 18 April 2009, Canada. Todd Litman, Robin Blair, Bill Demopoulos, Nils Eddy, Anne Fritzel, Danelle Laidlaw, Heath Maddox, Katherine Forster.
  • Wang, Q., Liu, H., Gao, K., & Zhang, L. (2019). Improved multi-agent reinforcement learning for path planning-based crowd simulation. IEEE Access, 7, 73841-73855.
  • Zazzi, M., Ventura, P., Caselli, B., & Carra, M. (2018). GIS-based monitoring and evaluation system as an urban planning tool to enhance the quality of pedestrian mobility in Parma. In Town and Infrastructure Planning for Safety and Urban Quality (pp. 87-93). CRC Press.

A Transportation Demand-Focused Environmental Approach On Determining The Main Axes Of Pedestrian Paths

Yıl 2023, Cilt: 5 Sayı: 1, 49 - 67, 01.05.2023
https://doi.org/10.53472/jenas.1248635

Öz

Pedestrian route planning is generally handled in areas where current pedestrian movements are concentrated. In addition, it is considered within the scope of accessing facilities with high land use attractiveness. Planning the main axes means actually planning the basic spine in the emergence of the pedestrian network. While determining the main axes, focusing on the elements with land use attractiveness or only the center with dense urban activity may not always give the right result. Instead, it may be preferable to prioritize urban transportation zonal demands. Thus, transitions from other modes of transport to pedestrian type may be encouraged more. To propose pedestrian axes in line with home-work and home-school demands or to reinforce them with social/physical infrastructure that may be preferred over other transportation modes will definitely encourage transitions between transportation modes. The policy of encouraging transitions from other modes by increasing the features such as comfort-aesthetics-functionality in the proposed routes should be adopted. In this study, it is aimed to generate the main pedestrian routes that will increase the transition to pedestrian mode. In this direction, a new approach has been generated in which the routes are determined by using the transportation master plan data. First, axes and zones with high urban access demand were identified. Walkable distances and transportation habits were evaluated. An approach has been developed that encourages pedestrian-mode.

Kaynakça

  • Adinarayana, B., & Mir, M. S. (2021). Modeling and application of AHP approach for development of pedestrian safety index (PSI) model for safety of pedestrian flows in urban areas of developing countries. Innovative Infrastructure Solutions, 6(3), 1-14.
  • Aultman-Hall, L., Roorda, M., & Baetz, B. W. (1997). Using GIS for evaluation of neighborhood pedestrian accessibility. Journal of urban planning and development, 123(1), 10-17.
  • Aydemir, P. K., Yılmazsoy, B. K., Akyüz, B., & Akdemir, Ç. (2018). Kentsel Ulaşımda Yaya Öncelikli Planlama/Tasarım Ve Transit Odaklı Gelişimin Metropol Kentlerdeki Deneyimi, İstanbul Örneği. Kent Akademisi, 11(4), 523-544.
  • Berg, A., & Newmark, G. L. (2020). Incorporating equity into pedestrian master plans. Transportation research record, 2674(10), 764-780.
  • Ceylan, H. & Gulhan, G., (2017). Denizli'nin Kentiçi Ulaşım Altyapısı, Ulaşımın Planlama Süreçleri ile Etkileşimi ve Geleceği. Denizli Kent Ekonomisi, Denizli Basımevi.
  • Chin, K. K., & Menon, G. (2015, June). Transport accessibility and infrastructure in Singapore–pedestrian facilities. In Proceedings of the Institution of Civil Engineers-Municipal Engineer (Vol. 168, No. 2, pp. 133-139). Thomas Telford Ltd.
  • Clifton, K., Singleton, P. A., Muhs, C. D., & Schneider, R. J. (2015). Development of a pedestrian demand estimation tool.
  • Coza, H., (2019). Denizli’de Yönetmeliklerin Nitelikli ve Özgün Konut Tasarımına Etkisi. Ege Mimarlık, Mimarlar Odası İzmir Şubesi, 2019/2-103, 39-43.
  • Desyllas, J., Duxbury, E., Ward, J., & Smith, A. (2003). Pedestrian demand modelling of large cities: an applied example from London
  • Dhanani, A., Tarkhanyan, L., & Vaughan, L. (2017). Estimating pedestrian demand for active transport evaluation and planning. Transportation research part A: policy and practice, 103, 54-69.
  • Dilip, A., ‘Complete street planning workbook’, The Institute for Transportation and Development Policy, Bundestag, (2009).
  • DUAP, 2010. Denizli Ulaşım Ana Planı. Denizli Belediyesi.
  • Gaputra, A. D., Widiastuti, I., & Estika, N. D. (2020, July). The Implementation of Transit-Oriented Development Concepts on Pedestrian Pathways in the City of Bandung. In IOP Conference Series: Earth and Environmental Science (Vol. 532, No. 1, p. 012019). IOP Publishing.
  • Gulhan, G., & Ceylan, H. (2016). Relation Between Land Use and Transportation Planning in the Scope of Smart Growth Strategies: Case Study of Denizli, Turkey. Sustainable Urbanization. IntechOpen, ISBN: 978-953-51-2652-2. Chapter 14.
  • Gültekin, B., “Kent İçi Yolların Yaya Kullanımına Yönelik Değerlendirilmesinde Çözümlemeli Bir Yaklaşım: Adana Örneği” Yüksek Lisans Tezi, Çukurova Üniversitesi Fen Bilimleri Enstitüsü, Adana, (2007).
  • Hoogendoorn, S. P., & Bovy, P. H. (2004). Pedestrian route-choice and activity scheduling theory and models. Transportation Research Part B: Methodological, 38(2), 169-190.
  • Hydén, C., ‘Walkıng’, Department of Traffıc Plannıng and Engıneerıng, Helsınkı, (1999).
  • Jabbari, M., Fonseca, F., & Ramos, R. (2018). Combining multi-criteria and space syntax analysis to assess a pedestrian network: The case of Oporto. Journal of Urban Design, 23(1), 23-41.
  • Kasemsuppakorn, P., & Karimi, H. A. (2013). A pedestrian network construction algorithm based on multiple GPS traces. Transportation Research Part C: Emerging Technologies, 26, 285-300.
  • Kim, B., & Pineau, J. (2016). Socially adaptive path planning in human environments using inverse reinforcement learning. International Journal of Social Robotics, 8(1), 51-66.
  • Larco, N., Steiner, B., Stockard, J., & West, A. (2012). Pedestrian-friendly environments and active travel for residents of multifamily housing: The role of preferences and perceptions. Environment and Behavior, 44(3), 303-333.
  • Lerman, Y., Rofè, Y., & Omer, I. (2014). Using space syntax to model pedestrian movement in urban transportation planning. Geographical Analysis, 46(4), 392-410.
  • Lilasathapornkit, T., Rey, D., Liu, W., & Saberi, M. (2022). Traffic assignment problem for footpath networks with bidirectional links. Transportation Research Part C: Emerging Technologies, 144, 103905.
  • McDonald K., Walk&roll: Memphıs regıon pedestrıan and bıcycle plan, Memphıs Urban Area Metropolıtan Plannıng Organizatıon, Florıda, (2020).
  • Mıtchell K., ‘Plannıng for walkıng’, Chartered Institution of Hıghways & Transportatıon, London, (2015).
  • Mohammad Azlan, A. I., & Naharudin, N. (2020). Measuring safety index for pedestrian path by using AHP-GIS. Built Environment Journal (BEJ), 17(3), 67-75.
  • Moore, R. L. (1953). Pedestrian choice and judgment. Journal of the Operational Research Society, 4(1), 3-10.
  • Nazir M.I., Al Razi K.M.A, Hossain, Q.S., Adhikary, S.K. (2014). Proceedings of the 2nd International Conference on Civil Engineering for Sustainable Development(ICCESD-2014), 14~16 February 2014, KUET, Khulna, Bangladesh, ISBN: 978-984-33-6373-2
  • Perotte, P., ‘Bıcycle and pedestrian master plan’, California, (2018).
  • Saunders, L. E., Green, J. M., Petticrew, M. P., Steinbach, R., & Roberts, H. (2013). What are the health benefits of active travel? A systematic review of trials and cohort studies. PloS one, 8(8), e69912.
  • Sayyadi, G., & Awasthi, A. (2013). AHP-based approach for location planning of pedestrian zones: Application in Montréal, Canada. Journal of transportation engineering, 139(2), 239-246.
  • Tal, G., & Handy, S. (2012). Measuring Non-motorized Accessibility and Connectivity in a Robust Pedestrian Network. Transportation Research Record, 2299(1), 48–56. https://doi.org/10.3141/2299-06
  • Terh, S. H., & Cao, K. (2018). GIS-MCDA based cycling paths planning: a case study in Singapore. Applied Geography, 94, 107-118.
  • Trinh, T. T., Vu, D. M., & Kimura, M. (2020, March). A pedestrian path-planning model in accordance with obstacle's danger with reinforcement learning. In Proceedings of the 2020 The 3rd International Conference on Information Science and System (pp. 115-120).
  • TÜİK, 2019. Denizli İli Nüfus Verileri. Ünal Çilek, M. (2020). Kamusal Alanlara Erişimde Optimum Yaya Güzergâhı Konforunu Belirlemeye Yönelik Kavramsal Bir Yaklaşım. Megaron,15(3):490-507.
  • Victoria Transport Institute. Pedestrian and Bicycle Planning Guide to Best Practices. 18 April 2009, Canada. Todd Litman, Robin Blair, Bill Demopoulos, Nils Eddy, Anne Fritzel, Danelle Laidlaw, Heath Maddox, Katherine Forster.
  • Wang, Q., Liu, H., Gao, K., & Zhang, L. (2019). Improved multi-agent reinforcement learning for path planning-based crowd simulation. IEEE Access, 7, 73841-73855.
  • Zazzi, M., Ventura, P., Caselli, B., & Carra, M. (2018). GIS-based monitoring and evaluation system as an urban planning tool to enhance the quality of pedestrian mobility in Parma. In Town and Infrastructure Planning for Safety and Urban Quality (pp. 87-93). CRC Press.
Toplam 38 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Çevre Mühendisliği
Bölüm Tüm Makaleler
Yazarlar

Esma Akbaş 0000-0002-5220-0245

Görkem Gülhan 0000-0003-2715-0984

Yayımlanma Tarihi 1 Mayıs 2023
Yayımlandığı Sayı Yıl 2023 Cilt: 5 Sayı: 1

Kaynak Göster

APA Akbaş, E., & Gülhan, G. (2023). Yaya Yolu Ana Akslarının Belirlenmesinde Ulaşım Talebi Odaklı Çevresel Yaklaşım. JENAS Journal of Environmental and Natural Studies, 5(1), 49-67. https://doi.org/10.53472/jenas.1248635

JENAS | Journal of Environmental and Natural Studies