Synergy Mechanism Between Cross-Domain Autonomous Driving in Urban Rail Transit and Urban Development a Comparative Case Study of Major Urban Agglomerations in China

Urban rail transit systems in China are rapidly evolving toward higher levels of automation and cross-domain integration. Cross-domain autonomous driving (CAD) represents a strategic breakthrough that enables automated operations across multiple lines, operators, and administrative regions. However, the synergy mechanism between CAD and metropolitan development remains insufficiently explored. This study constructs an integrated synergy framework grounded in Complexity Science, Collaborative Governance Theory, and Core–Periphery Theory, revealing how CAD enhances operational resilience, governance coordination, and spatial integration. Using the Beijing–Tianjin–Hebei region, the Yangtze River Delta, and the Guangdong–Hong Kong–Macao Greater Bay Area as comparative cases, the analysis demonstrates that CAD reduces energy consumption by up to 18%, improves real-time scheduling stability, strengthens cross-jurisdictional compatibility, and accelerates regional spatial restructuring. The findings provide theoretical and empirical support for advancing cross-domain intelligent rail integration in China’s metropolitan clusters.