Speakers
Description
Street experiments are increasingly adopted as planning measures to help communities visualize “radically different arrangements of the urban mobility system”(Bertolini 2020). These interventions foster active mobility and public life through relatively short-term, low-resource, and small-scale spatial transformations that enable “here and now” changes to streetscapes. Despite their potential, such transformations often require significant spatial interventions, resources, and institutional and community support. Inadequate or unresponsive design remains a recognized barrier to their broader implementation (VanHoose 2023).
The recent rise of generative artificial intelligence (GenAI) tools promises to disrupt how cities are planned and designed. Some of these tools aim to empower diverse stakeholders to “reinvent their streets” while creating “happier and healthier environments” (NL Netherlands 2025). For instance, certain tools visualize how adopting a cycling lifestyle or adding outdoor seating could transform a specific street. As educational exercises, GenAI tools offer opportunities to envision alternative futures. However, mobility injustice remains a pressing concern, underscoring the need for planners to critically engage with these technologies.
In this presentation, we draw on our experience designing and teaching a course focused on fostering critical skills for engaging with GenAI in urban design. Using relevant frameworks, we discuss how these tools can be integrated into planning education, emphasizing the need to analyze their outputs critically and understand their potential impacts on urban mobility and equity.
References
Bertolini, Luca. 2020. “From ‘Streets for Traffic’ to ‘Streets for People’: Can Street Experiments Transform Urban Mobility?” Transport Reviews 40 (6): 734–53. https://doi.org/10.1080/01441647.2020.1761907.
NL Netherlands. 2025. “Reinvent Your Street.” Https://Dutchcyclinglifestyle.Com/. 2025.
VanHoose, Katherine. 2023. “City Street Experiments and System Change: Identifying Barriers and Enablers to the Transformative Process.” Transportation Research Interdisciplinary Perspectives 22 (November). https://doi.org/10.1016/j.trip.2023.100982.
Keywords | Street experiments; generative artificial intelligence; planning education |
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Best Congress Paper Award | Yes |