Comparative Review of AI Applications in Urban Transport: Insights from China’s City Brain and Singapore’s LTA Smart Mobility

Abstract

In recent years, cities around the world have increasingly turned to artificial intelligence (AI) as a means to address pressing challenges in urban mobility, traffic congestion, and emergency response management. Recent literature shows that AI-driven transportation systems have yielded notable improvements in traffic efficiency, commuter satisfaction, and the pursuit of sustainable mobility in both developed and developing contexts. Among the most prominent examples are China’s City Brain, developed by Alibaba Cloud, and Singapore’s Smart Mobility 2030 strategy, led by the Land Transport Authority (LTA). This review fills a gap in cross-national comparative studies by examining the technical architectures and operational outcomes of these systems and analyzing how governance structures, policy frameworks, and socio-cultural contexts shape their deployment. Drawing on peer-reviewed literature, policy documents, and official reports, the study proposes a multi-dimensional analytical framework for evaluating AI applications in urban transport, offering practical insights and policy implications.