Understanding Demand for Shared Autonomous Micro-Mobility

TL;DR

This paper investigates how shared autonomous micro-mobility, especially autonomous bicycles, influences travel behavior, environmental impacts, and user adoption, emphasizing the importance of service design and demographic factors.

Contribution

It introduces a context-aware stated preference survey and discrete choice models to analyze user preferences and environmental impacts of autonomous micro-mobility services.

Findings

High adoption with minimal wait and cost increases emissions.

Moderate wait times can reduce environmental impacts.

Adoption varies by demographic and city context.

Abstract

This study examines the behavioral and environmental implications of shared autonomous micro-mobility systems, focusing on autonomous bicycles and their integration with transit in the U.S. While prior research has addressed operational and lifecycle aspects, a critical gap remains in understanding which modes these services are likely to substitute, who is most inclined to adopt them, and how service attributes influence user decisions. We design a context-aware stated preference survey grounded in real-world trips and estimate discrete choice models, including a hybrid model incorporating latent attitudes. Findings indicate that adoption, mode shift, and environmental impacts are highly sensitive to service design. Scenarios with minimal wait and cost yield high adoption but increase emissions, while moderate waits are more likely to reduce impacts. Adoption likelihood varies with demographic characteristics, and outcomes depend on city type, context, and infrastructure assumptions. These insights can inform the development of more sustainable and equitable mobility systems.