Algorithmic Governance in Urban Mobility: The Role of Artificial Intelligence in Public Transport Decision Making

Abstract

The emergence of Artificial Intelligence (AI) is reshaping urban mobility governance, promising unprecedented optimization in public transport decision-making. This transition to "algorithmic governance" raises questions about its real impact beyond operational efficiency. The objective of this study is to critically analyze the scientific literature (2020-2025) to assess the balance between techno-economic advances and socio-political challenges (equity, transparency, and accountability) in the implementation of AI in public transport management. A systematic literature review (SLR) methodology was implemented under the PRISMA protocol. Eighty-nine articles extracted from Scopus and Web of Science were analyzed using critical thematic analysis to identify dominant paradigms and research gaps. The results reveal a hegemonic bias (85% of the studies) toward "technological solutionism," focused on route optimization and the reduction of operating costs (Ye & Hu, 2023). There is a severe lack of research on algorithmic auditing mechanisms and participatory governance frameworks. We conclude that the inherent opacity (the "black box" problem) and the prioritization of efficiency over social equity (Höglund, 2023) are generating new forms of digital exclusion and weakening public decision-making sovereignty. Academia is urged to reorient research toward algorithmic justice in mobility.