A generative design project from Independent Study to help urban planners explore alternative motorway networks after removing highways that have caused societal problems. Removing highways are understudied in may US cities to improve quality of life in communities. This tool was coded from scratch with Python. Geospatial data were extracted from open source API, analyzed by Geopandas and NetworkX, python libraries specialized in data manipulation or network analysis. The core features were finished so that the program can specify an area, detect and cut highways, simulate vehicle travels and visualize the result such as congestion. I'm working on improvement of data visualization, user interface or application of machine learning to bring it to life at high fidelity.

The Space Between : The big context of this project is how to decentralize the automotive transportation system. From my professional experiences in the transportation industry, I believe that the current system creates inequity, causes human injuries and death, and exhausts tons of greenhouse gases for the sake of freedom of mobility.

Whereas many cities have committed to, or are planning, or studying, highway removal for community re-connection, equitable housing, livable spaces, and so forth in the next ten to fifteen years, most of the highway removal projects, including past ones, are not truly removing highways but rerouting the roads to other places or underground, or transforming them into boulevards, where cars can still run. There is not much research to study the side effects of the removal on transportation operations, such as congestion, either. I hope the tool will give inspiration of how to accelerate the car-decentralized future.

Designers : Shinichiro Kuwahara

Course : Independent Study

Instructors : Mark Jones, Zach Pino