Urban transportation systems are undergoing a critical transformation driven by advances in artificial intelligence (AI). Despite many technical and theoretical discussions of AI technologies and a few case studies of AI implementation in selected cities, there remains a large gap in our knowledge about the landscape of the adoption of AI in urban mobility. This study narrows this gap by addressing: where, when, how, and for which modes is AI being integrated into urban mobility across Europe? By text mining authoritative and publicly available data sources, i.e., EU Urban Mobility Observatory and official city websites, complemented by manual content analysis, this work documents the geographic distribution, temporal trends, use cases, and transportation modes of AI adoption. As of September 2025, I identified 88 AI deployments across 73 cities in 21 European countries. It shows a clear acceleration in adoption after 2022, peaking in 2024 and remaining high in 2025. The deployments fall into eight broad categories: traffic monitoring and management; transport infrastructure condition assessment; parking management; improving bus and bike sharing systems; traffic control; autonomous and new mobility systems; data integration and digital twins; and public-facing digital services. In terms of transport mode, adoption is road-centric, with road applications accounting for 89% of recorded cases, while rail, air, waterborne, and cross-modal deployments are relatively rare. The compiled data is openly available online. This work is among the first efforts to establish an empirical base for assessing the prevalence of AI in urban mobility. It aims to provide urban planners, policymakers, and researchers with a better understanding of current AI adoption practices in the European context.
Meng Cai (Tue,) studied this question.