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Journal

2015 | 1(41) | 119-128

Article title

Generatywna optymalizacja w planowaniu przestrzennym – koncept miasta przyjaznego ruchowi pieszemu

Authors

Content

Title variants

EN
Generative design optimization in urban planning – walkability-optimized city concept

Languages of publication

Abstracts

EN
This paper presents an urban analysis and design workflow using Rhinoceros/Grasshopper with evolutionary solver Galapagos and add-ons: Shortest Walk (ShortWalk) and Elk. The research is based on the authentic urban situation in the city of Irkutsk and was conducted within the 15th session of the International Baikal Winter University of Urban Planning 2014. The aim of the research is to propose a workflow, which reforms some part of the existing urban structure into walkable neighborhood. The study uses a walkability calculator to estimate the walk scores for the residential buildings within the design perimeter and applies genetic algorithms to point out the location of the new amenities to maximize the average of the particular walk scores. As a result, the conceptual project of walkable-optimized neighborhood is proposed. The conclusions show the limitations and potentials of the applied algorithm, discuss the resulting project and outline future research.
PL
W artykule zaprezentowano analizę urbanistyczną oraz koncepcyjny projekt stworzony z użyciem oprogramowania Rhinoceros/Grasshopper, solvera Galapagos oraz wtyczek ShortWalk i Elk. Badania zostały przeprowadzone w ramach 15. sesji międzynarodowych warsztatów International Baikal Winter University of Urban Planning 2014 i bazują na autentycznym kontekście urbanistycznym Irkucka (luty 2014). Celem pracy jest zaproponowanie algorytmu optymalizacyjnego, który pozwoli na przekształcenie istniejących struktur urbanistycznych w dzielnice osiągalne na piechotę. Stworzony na potrzeby projektu algorytm w aplikacji Grasshopper wykorzystuje zaadaptowany kalkulator przyjazności dla pieszych (oryginalnie WalkScore®) do oszacowania wyników walk score dla poszczególnych zabudowań mieszkalnych, a następnie przy użyciu ewolucyjnego narzędzia do rozwiązywania matematycznych problemów wyszukuje optymalne lokalizacje dla nowych funkcji usługowych w taki sposób, aby zmaksymalizować średnią wyników walk score. Jako wynik implementacji algorytmu w zadanym problemie w dalszej części artykułu przedstawiono konceptualny projekt przyjaznej ruchowi pieszemu dzielnicy. We wnioskach przedyskutowano zalety i wady zaproponowanego algorytmu, wynikowy projekt, a także wskazówki dla dalszych badań.

Journal

Year

Issue

Pages

119-128

Physical description

Dates

published
2015

Contributors

author
  • Wydział Architektury Politechniki Wrocławskiej/Faculty of Architecture, Wrocław University of Technology.

References

  • [1]  Sohn D.W., Moudon A.V., Lee J., The economic value of walkable neighborhoods, „URBAN DESIGN International” 2012, No. 17, 115–128.
  • [2]  The Mayor of London and Transport for London, Making London a Walkable City: The Walking Plan for London, Transport for London, 2004.
  • [3]  Abley S., Walkability Scoping Paper, 21 March 2005. http://www. levelofservice.com/walkability-research.pdf [accessed: 21.03.2014].
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  • [5]  Handy S., Smart growth and the transportation – land use connection: What does the research tell us?, „International Regional Science Review” 2005, No. 28(2), 146–167.
  • [6]  Dorn J., Hidden in Plain Sight: Capturing the Demand for Housing Near Transit, [Center for Transit-Oriented Development Oakland] 2004.
  • [7]  Shapiro R.J., Hassett K.A., Arnold F.S., Conserving Energy and Preserving the Environment: The Role of Public Transportation, [American Public Transportation Association, Washington] 2002.
  • [8]  Rakha T., Reinhart C., Generative urban modeling: a design work flow for walkability-optimized cities, Massachusetts Institute of Technology, Cambridge, Submitted to SimBuild 2012.
  • [9]  American Community Survey, 2004 American Community Survey National Survey on Communities, 2004, Conducted for Smart Growth America and National Association of Realtors, http://www.brspoll. com/uploads/files/Smart%20Growth.pdf [accessed: 21.03.2014].
  • [10]  Allen A.T., Ovsyannikova T.Y., Prazukin D.K., Worzala E., The Development of a Residential Real Estate Market in Russia, „Journal of Real Estate Literature” 2004, Vol. 12, No. 3, 363–374.
  • [11]  Khomutinnikov I., Perestroika – Development and transformation of urban space, Analysis report/Document No 2 for the International Baikal Winter University of Urban Planning 2014, 15th Session, 1–21 February 2014, ФГБОУВПО Irkutsk State Technical University, 4.
  • [12]  Khotulev R., Perestroika – Development and transformation of urban space, Analysis report/Document No 2 for the International Baikal Winter University of Urban Planning 2014, 15th Session, 1–21 February 2014, ФГБОУВПО Irkutsk State Technical University, 5.
  • [13]  Duncan D.T., Aldstadt J., Whalen J., Melly S.J., Gortmaker S.L., Validation of Walk Score® for Estimating Neighborhood Walkability: An Analysis of Four US Metropolitan Areas, „International Journal of Environmental Research and Public Health” 2011, No. 8, 4160–4179.
  • [14]  Dechter R., Pearl J., Generalized best-first search strategies and the optimality of A*, „Journal of the ACM” 1985, Vol. 32, Iss. 3, 505–536. [15]  Knoblauch R.L., Pietrucha M.T., Nitzburg M., Field Studies of Pedestrian Walking Speed and Start-Up Time, „Transportation Research Record” 1996, No. 1538, 27–38.
  • [16]  FHWA, Manual on Uniform Traffic Control Devices for Streets and Highways (MUTCD), The Federal Highway Administration (U.S. Department of Transportation) 1988.
  • [17]  Carr L.J., Dunsiger S.I., Marcus B.H., Walk score™ as a global estimate of neighborhood walkability, „American Journal of Preventive Medicine” 2010, No. 39(5), 460–463.

Document Type

Publication order reference

Identifiers

Biblioteka Nauki
293886

YADDA identifier

bwmeta1.element.ojs-doi-10_5277_arc150110
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