Car Centric Development

Cars completely swamped cities in the 20th century, bringing with them congestion, air pollution, noise, and greenhouse gases. Now Barcelona is implementing an urban plan that would decisively change that, pushing cars off most streets and turning the land over to citizens for mixed-use public spaces, or the so called “superblocks.”

Superblocks are neighbourhoods of nine blocks, where traffic is restricted to major roads around the outside, opening up entire groups of streets to pedestrians and cyclists. The aim is to reduce pollution from vehicles, and give residents much-needed relief from noise pollution. They are designed to create more open space for citizens to meet, talk and do activities.

Car Ownership Correlation

The speed of vehicle ownership expansion in emerging market and developing countries has important implications for transport and environmental policies, as well as the global oil market. In relation to the current development of Barcelona Superblocks, this project’s aim is to find out the correlation between the number of population compared to vehicle ownership by type of each neighborhood. With the expectation to gain empirical study which can be used to predict what type of vehicle is mostly owned in a certain neighborhood and can then help the provision planning of Barcelona Superblock.


The dataset used in this project was a vehicle census data of each neighborhoods in Barcelona, that ranges from 2016 to 2019. The dataset includes; type of vehicle, name of neighborhood, year, and the quantity of each vehicle type.

Supervised Regression

Regression analysis is a subfield of supervised machine learning. It aims to model the relationship between a certain number of features and a continuous target variable. Having already a set of points, the regression algorithm will model the relationship between two variables, the (x) being the population density, and the (y) being the number of vehicle owned. In this experiment, car type is selected.

Post Pandemic Mobility

One of the sectors that has been the most hit by the lockdown measures and restrictions due to the current economic and humanitarian crisis has been Mobility. While cities are trying to reconfigure its urban landscapes to build more equitable mobility, the behavior of citizens when using transportation will also shift, both private and public actuators can leverage the momentum by focusing on this sector more attentively.

Predicting Car Ownership in Barcelona: Supervised Regression is a project of IAAC, Institute for Advanced Architecture of Catalonia developed at AI in Urbanism course of Master in City and Technology program in 2019-2021 by:
Student: Aryo Dhaneswara
Faculty: Angelos Chronis, Serjoscha Duering, Nariddh Khean’s.