Using AI for responsible mobility planning in livable cities
Global urbanization and the growth of cities are leading to a sharp increase in mobility and logistics, while available space is scarce. Municipalities face major challenges, such as creating sustainable mobility systems, maintaining infrastructure, and ensuring quality of life. When designing these complex systems, a wide range of parties work together, sometimes with conflicting interests. This can lead to socially unjust outcomes.
The role of AI in mobility planning and urban design
Artificial intelligence can support policymakers and urban planners in designing mobility systems in complex urban environments. Digital twins can generate and explore design options, rather than solely analyzing the effects of existing plans. This makes it possible to investigate more alternatives and guide stakeholders in making informed choices.
At the same time, the use of AI entails risks. Biases in data and models can lead to unequal access to mobility services. Choices made in traffic management and spatial planning can also unintentionally reinforce existing inequalities. This calls for careful research into the ethical, legal, and social consequences of AI before these systems are deployed on a large scale.
About the ELSA Lab Mobility DesAIgn
The ELSA Lab Mobility DesAIgn focuses on the ethical, legal, and societal implications of using digital twins with AI for urban mobility and spatial design. The lab builds knowledge and methods to apply AI responsibly and with societal support, so that stakeholders gain insight into how data, models, and algorithms influence mobility policy.
The lab approaches digital twins not as tools that deliver a single optimal design, but as aids that enable stakeholders to jointly explore and optimize designs based on their preferences and constraints. This human-centered approach differs from traditional design methods, in which technology often plays a dominant role.
Guiding responsible AI in mobility planning
The lab focuses on three related use cases: sustainable mobility, car-restrictive measures, and future traffic management with connected and autonomous vehicles. Within these use cases, the lab is working on, among other things:
- Ethical and social objectives for design and evaluation methods
- Transparent and robust AI recommendation systems without hidden assumptions.
- Legal and ethical frameworks in line with the AI Regulation and future regulations.
- Practical methodologies for collaborative experimentation with AI-supported policy decisions.
- Design sessions in which stakeholders jointly explore the effects of mobility choices.
This multidisciplinary research is linked to practical settings in Amsterdam and South Holland, allowing insights to be developed and shared iteratively.
Collaboration partners
Research organizations, companies, governments, and networks collaborate within the lab, including TNO, TU Delft, Leiden University, BAM, Goudappel, Vervoerregio Amsterdam, and various innovation partners.
Want to know more or collaborate?
Are you interested in the ELSA Lab Mobility DesAIgn? Or would you like to participate in the design sessions or collaborative activities as a researcher, company, or government agency? Please contact us via theTNO website. Here you will find all the opportunities for collaboration and knowledge sharing.
