Reliability in large-scale rail systems is shaped by infrastructure condition, operational complexity, and network interdependence. The New York metropolitan rail network, comprising the New York City Subway, Long Island Rail Road, Metro-North Railroad, New Jersey Transit, and Amtrak, represents one of the most complex and highly utilized rail systems globally. This study develops an integrated reliability engineering framework combining panel regression, count-based modeling, and Monte Carlo simulation to evaluate system performance. This work has used a multi-source secondary dataset prepared from publicly available operational and performance reports from January 2023 till December 2025 across the five major rail systems. Results identify infrastructure failures, shared-corridor exposure, and network topology as the primary determinants of unreliability. While commuter rail systems exhibit high on-time performance (>95%), their reliability remains structurally dependent on shared infrastructure, whereas the subway demonstrates lower performance (~82%) due to high-frequency operations and sensitivity to disruptions. Simulation results further reveal that critical nodes, including major terminals and tunnel crossings, generate disproportionate delay propagation effects, highlighting the role of network centrality and cascading failures. The findings demonstrate that rail reliability is fundamentally a network-level phenomenon. Improving performance requires corridor-level planning, targeted infrastructure investment, and integrated governance frameworks that address interdependencies across operators.
Keywords