Description
Urban planning is a complex problem and street network is a major part of it. Urban planning disciple had a common understanding that algorithms have the potential to tackle complex problems. However, the difficulty of real-world application in urban planning has been overlooked. As algorithmic street network proposals can improve current urban planning, what has stopped them from being approved and built? Then, this paper attempts to understand what types of street networks urban planners are looking for, followed by identification of the potential uses of algorithmic-generated geometries according to their actual street network performance. Research methods involve two cases of algorithmic street network proposals and street network simulations on six cities and five algorithmic-generated geometries. Case studies show how urban planners were commonly dismissive of user acceptance and existing context during algorithmic-planning process. The algorithmic-planning process was significantly more time-consuming than the ones which were not algorithmic-driven. The level of project completion was then traded off noticeably. Case studies of existing cities reflect that mesh-type street networks provide better connectivity comparing to grid-type network. After algorithmic-generated geometries connectivity simulations, the results were then applied to a studio project. It illustrated a potential research-planning process for street network planning, as a baseground for future urban planners. | Period | Jul 2021 |
|---|