Rapid urbanization and increasing travel demand in the metropolitan area of Tehran have intensified challenges such as traffic congestion, air pollution, high energy consumption, and growing pressure on the public transport network. In this context, autonomous rail transit (ART), as one of the emerging intelligent transport technologies, offers significant potential to enhance the efficiency, safety, and sustainability of urban transport systems.This study aims to conduct a multidimensional assessment of the impacts and requirements of implementing ART in Tehran’s rail network. The research adopts a mixed-methods approach, combining a systematic literature review, semi-structured expert interviews, SWOT analysis, and the Analytic Hierarchy Process (AHP).The results indicate that the implementation of ART can reduce train headways and increase network passenger capacity by approximately 30%. In addition, rail automation improves service reliability and reduces energy consumption through optimized operations and the reduction of human errors. Findings show that the operational-traffic dimension, with a weight of 0.34, is the most influential factor in evaluating ART in Tehran.Despite its significant benefits, challenges such as high initial investment costs, legal and regulatory gaps, cybersecurity risks, and the need for public acceptance remain major barriers to its deployment. Based on the results, a phased and pilot-based implementation strategy, along with the development of institutional, legal, and financial infrastructures, is proposed as the most realistic pathway for transitioning to autonomous rail transit in Tehran.