A methodology for urban planning generation: A novel approach based on generative design

Abstract

The construction sector is undergoing a digital transformation that aims to increase productivity, improve processes and take advantage of the new advances in digitalization. Urban planning is particularly susceptible of benefiting from these advances due to its complexity and the large amount of data and disciplines that come together. In this paper, we propose a novel methodology that aims to enhance current urban planning design methods, which are mainly designed by a planner, to an optimized process where the planner interacts with a software that automates many of the tasks. This methodology based on generative design principles, develop urban design solutions by subdividing a given plot and assigning different housing typologies on it. Our proposed software requires 3D urban models datasets as a reference to create solutions within a specific shape, style, proportions, among others, as well as input from the planner to guide the program according to project requirements and existing local norms. Higher automation in the design process eases project changes and allows for more and varied design testing, which in the end, contributes to better analysis and decision making. We tested our proposal in a case study in the city of Vienna to illustrate the design process, obtain several urban planning solutions and validate our methodology.