CityAI Lab: "A place where data, AI and behavioural theory come together"

Cities are hotspots of human activity that have increased our prosperity, happiness, and health. Yet the future liveability of cities around the world is under pressure as they face major social-technical challenges. Those challenges include crumbling social cohesion, income inequality, overcrowding of public spaces, and unhealthy local environments caused by factors such as heavy traffic and noise pollution. CityAI Lab examines the pivotal role that the urban environment plays in tackling such challenges.

Our research focuses on unravelling how the urban environment and human behaviour dance a tango. It capitalises on advances in machine learning and on the wealth of data available now at a city level. We combine these with established theories on planning and behaviour, hoping to contribute to the development of more attractive and liveable cities.

The CityAI Lab is part of the TU Delft AI Labs programme.

PhD Research Projects

Click on one of the projects to learn more about what we are doing at the CityAI Lab.

Using artificial intelligence to comprehend, automate and assist choice modellers` decisions
Urban factors shaping residential segregation patterns in cities
Vehicle coordination in urban traffic: a perspective from human behaviour and decisions
Understanding the relationships between urban space, perceptions and behaviours using urban embeddings
Listening to our Cities:
Using Smart Sensors and Machine Learning to Study Urban Noise Pollution
Diabolical dilemmas in allocating scarce health resources:
Combining choice modelling and machine learning to develop models of moral choice behaviour

Highlights

CityAI lab collaborates with Municipality of Rotterdam and EUR on urban liveability

May 2024 - The Municipality of Rotterdam, Erasmus University Rotterdam (EUR), and the Delft University of Technology (TUD) have initiated a new collaboration centred around the topics of liveability and smart asset management. The project, called “Urban Intelligence for Liveability and Asset Management“, aims to improve the liveability of outdoor urban spaces and spans 2.5 years. The key idea is to leverage AI and urban data analytics to develop new strategies for increasing the city’s liveability while considering asset maintenance costs. At the heart of the collaboration lies the Municipality of Rotterdam’s commitment to enhancing the quality of life for its citizens and addressing the structural challenges in asset management stemming from, inter alia, climate change, changing population demographics and urbanisation trends. Click here for more information.

New paper published on the evolution of residential segregation

April 2024 - The paper investigates the evolution of residential segregation patterns in the Netherlands in the period 2015 - 2020, with a focus on the population with a non-western migration background. It is published (open-access) in the journal Cities. Here is the link to our paper.

Lion Cassens wins Responsible Solutions in the Smart City challenge!

Dec 2023 - The Responsible Sensing Lab -an initiative by Amsterdam Institute for Advanced Metropolitan Solutions (AMS) and the City of Amsterdam - announced Lion Cassens as one of the winners of their call for proposals: Responsible Solutions in the Smart City. The jury believes his project, which involves using smart noise sensors to map the perceived noise soundscapes in urban environments- offers an innovative idea to bridge the gap between public values and smart city technology. The Responsible Sensing Lab will provide financial support and resources to transform the ideas into a tangible prototype in the city of Amsterdam. In the months ahead, Lion will work with the AMS and the municipality of Amsterdam to roll out a network of noise sensors. See the full announcement here.

The Team

Directors

Sander van Cranenburgh

Faculty of TPM
Lab director

Simeon Calvert

Faculty of CEG
Lab director

Oded Cats

Faculty of CEG
Lab director


PhD Candidates

Lucas Spierenburg

PhD Candidate

Yiru Jiao

PhD Candidate

Lion Cassens

PhD Candidate

Gabriel Nova

PhD Candidate

Nicholas Smeele

PhD Candidate


Associated faculty

Maarten Kroesen

Associated Faculty

Hans van Lint

Associated Faculty


Current master students

Bert Berkers

Master student

Esteban Ralon

Master student

Roos Terra

Master student

Lanlan Yan

Master student

Bastiaan Bakker

Master student