Generative Urban Modeling: A Design Work Flow for walkability-optimized cities Tarek Rakha and Christoph Reinhart Massachusetts Institute of Technology Department of Architecture Building Technology Program Sustainable Design Lab

Outline Introduction Urban Form Generation Methodology Generative Urban Form Workflow Walkability Assessment Optimization Urban Performance Application - Results Discussion Conclusion

Introduction United Nations, 2011. World Urbanization Prospects: The 2010 Revision. United Nations, New York. By the year 2050, the world population is projected to reach 10.1 billion!

Terrain morphology is often less benign to urban developments Introduction Terrain morphology is often less benign to urban developments

Introduction A comparison between minimally changed street structures in downtown Cairo, Egypt. (Left) Author adapted map of Cairo in 1933 (Nicohosoff, A., 1933). (Right) An online contemporary map of the same area (Bing Maps, 2011). A road network, once in place, tends to be remarkably resistant to change

Introduction – Previous Work Site design and its relationship to terrain in the third dimension has thus far been disregarded. Academic: Beirão, J. N., Nourian, P., Mashhoodi, B., 2011. Parametric urban design: an interactive sketching system for shaping neighborhoods. Professional: Growing Cities, SOM

Urban Form Generation Methodology Generative Urban Form Workflow Subdivide terrain following design logic. Manipulate the terrain. Set street widths offsets and building lots. Zone parametrically controlled building forms. Performance Evaluation Walkability, Daylighting Potential, Thermal Comfort Energy Efficiency Carbon Emissions Etc. Optimization Utilization of optimization schemes

Urban Form Generation Methodology Generative Urban Form Workflow Subdivide terrain following design logic. Manipulate the terrain. Set street widths offsets and building lots. Zone parametrically controlled building forms. Performance Evaluation Walkability, Daylighting Potential, Thermal Comfort Energy Efficiency Carbon Emissions Etc. Optimization Utilization of optimization schemes

Generative Urban Form Workflow The coding of an urban massing modeler that allows users to generate and manipulate massing models for multiple buildings is the essence of the tool. When an urban design is generated, it will be ready for identification of urban massing solutions that optimize various neighborhood performance metrics such as potential for pedestrian thermal comfort etc…

Load Terrain Subdivide Terra-Form Model Urban Mass

Load Terrain Data – Elevation Model

Subdivide Terrain

Subdivide Lots & Streets

Terra-Form

Add Buildings

Zoning

Parametric Tool Layout

Urban Form Generation Methodology Generative Urban Form Workflow Subdivide terrain following design logic. Manipulate the terrain. Set street widths offsets and building lots. Zone parametrically controlled building forms. Performance Evaluation Walkability, Daylighting Potential, Thermal Comfort Energy Efficiency Carbon Emissions Etc. Optimization Utilization of optimization schemes

Urban Form Generation Methodology Generative Urban Form Workflow Subdivide terrain following design logic. Manipulate the terrain. Set street widths offsets and building lots. Zone parametrically controlled building forms. Performance Evaluation Walkability, Daylighting Potential, Thermal Comfort Energy Efficiency Carbon Emissions Etc. Optimization Utilization of optimization schemes

Performance Evaluation: Walkability Walkability was consciously chosen as an initial sustainability performance indicator, since planning of urban density is a necessary step to contain urban growth. It constitutes a key challenge to sustainable urban developments worldwide.

Neighborhood Walkability Walkability is a measure of how friendly an area is to walking. Evaluating walkability is challenging because it requires the consideration of subjective factors. Factors influencing walkability include: The presence or absence and quality of footpaths, sidewalks or other pedestrian right-of-ways Traffic and road conditions Land use patterns Building accessibility and safety.

Street Smart Walkscore www.walkscore.com Walkability is linked to the density of amenities, number of intersections and block lengths.

Street Smart Walkscore Scaling Factor: less than ¼ mile 100%, more than 1.5 mile 0%

Street Smart Walkscore Walk Score of transit stations in Phoenix, AZ

Urban Form Generation Methodology Generative Urban Form Workflow Subdivide terrain following design logic. Manipulate the terrain. Set street widths offsets and building lots. Zone parametrically controlled building forms. Performance Evaluation Walkability, Daylighting Potential, Thermal Comfort Energy Efficiency Carbon Emissions Etc. Optimization Utilization of optimization schemes

Urban Form Generation Methodology Generative Urban Form Workflow Subdivide terrain following design logic. Manipulate the terrain. Set street widths offsets and building lots. Zone parametrically controlled building forms. Performance Evaluation Walkability, Daylighting Potential, Thermal Comfort Energy Efficiency Carbon Emissions Etc. Optimization Utilization of optimization schemes

Optimization: Genetic Algorithms Fitness function: Optimize walkscores to be more than 70 (very walkable).

Urban Performance Application Site Area: 1.45 km2 Max. Elevation: 360m Population: 21,600 people

Iterations against fitness function in walkability optimization

Population percentages against Walk score The calculated centroid of the three solutions was almost central to the terrain. Important amenities that give higher scores spread out. If entrances to buildings change, solutions that do not perform will achieve a better score that may be acceptable.

Discussion The scoring system is street dependent, meaning that walking distances from the housing unit to the street are ignored. Disregarding terrain when calculating the walk scores is a weakness. Utilization of automation procedures to generate form. The focus shifts to gaining insight into urban morphology and its effect on performance through iterative explorations and optimization procedures. Cultural adaptation.

Conclusion A new Urban Massing tool based on street gradients in hilly situations. A walkability calculation procedure for sustainable infrastructure assessment. Linking to GA’s for performance optimization. Moving forward to validations of walking/biking.

ACKNOWLEDGEMENTS The writing of this paper was supported by a grant from the Massachusetts Institute of Technology Energy Initiative (MITEI). The authors are indebted to Panagiotis Michalatos and Jon Sargent for their contributions to the development of the Grasshopper urban massing tool and the walkscore calculator, respectively. Generative Urban Modeling: A Design Work Flow for walkability-optimized cities Tarek Rakha (rakha@mit.edu) and Christoph Reinhart Massachusetts Institute of Technology Department of Architecture Building Technology Program Sustainable Design Lab