Special issue on AI-driven prediction and optimisation for smart rail transit systems

In the study of smart rail transit systems, demand prediction, operational optimisation, and resilient network planning are essential, as urban rail increasingly operates within complex multimodal and uncertain environments. This special issue highlights the role of artificial intelligence and large-scale data analytics in advancing smart rail transit, and examines the topic through forecasting, control, disruption management, multimodal coordination, and decision optimisation. The works comprising this special issue can thus provide ideas for future studies on intelligent rail operations and serve as a long-term reference for data-driven smart transportation systems.