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Shared autonomous bicycles could transform how we move through cities, but their impact depends on how they are designed and integrated. This project explores who adopts them, which trips they replace, and how service choices shape environmental outcomes.
As we explore new ways to move people efficiently and sustainably, shared autonomous micro-mobility, the MIT Media Lab City Science group has developed lightweight shared autonomous vehicles, such as the MIT Autonomous Bicycle Project or the Persuasive Electric Vehicle (PEV), as an alternative to traditional transport. This project investigates how these systems might reshape everyday travel behavior, both as a standalone mode and when integrated with public transit.
While our previous research focused on the technical performance and environmental footprint of these systems, less is known about how people would actually use them. Which trips would they replace? Who is most likely to adopt them? And how do factors like cost and waiting time influence these decisions?
To address these questions, we designed a context-aware survey based on participants’ real-world travel patterns. Using this data, we developed behavioral models that capture not only observable choices but also underlying attitudes toward autonomous technologies. This approach allows us to better understand how different users respond to new mobility options.
Our findings show that the impact of shared autonomous micro-mobility depends strongly on how the service is designed. Systems with very short wait times and low costs can attract high levels of adoption, but may unintentionally increase overall emissions by replacing more sustainable modes like walking or transit. In contrast, services with moderate wait times tend to encourage more balanced shifts, reducing environmental impacts while still providing convenience.
We also find that adoption varies across demographic groups and urban contexts, highlighting the importance of designing systems that are both equitable and responsive to local conditions. Infrastructure, city form, and integration with existing transit networks all play a critical role in shaping outcomes.
By linking user behavior with environmental performance, this project provides insights for designing shared autonomous mobility systems that support more sustainable, inclusive, and people-centered cities.