| Abstract |
This study proposes an analytical method and framework for evaluating disruptions in public transit systems during extreme weather events by utilizing General Transit Feed Specification Real-Time
(GTFS RT) data. The research tests the method, focusing on the operational impact of Hurricane Milton on the Central Florida Regional Transportation Authority (LYNX) in October 2024. Two resilience
metrics are introduced and applied: the Transit Disruption Severity Index (TDSI), which captures the severity of service interruptions, and the Area Under the Curve (AUC), which reflects the cumulative
extent of disruption across four defined operational phases: pre-hurricane, during the hurricane, the immediate aftermath, and the post-hurricane. Findings indicate that on October 9, the day of the hurricane, the transit system experienced a near-complete operational collapse, with the TDSI exceeding 0.8 and the AUC reaching a maximum of 10.38. Despite this disruption, services were restored to near-
normal levels within three days, demonstrating significant adaptive capacity. Notably, weather variables such as wind speed and precipitation showed limited statistical association with service degradation,
suggesting that institutional decisions and existing infrastructure vulnerabilities played a more decisive role in determining system performance. By integrating high-frequency operational data with resilience
assessment methods, this research offers a scalable and transferable approach for quantifying both the absorptive and adaptive capacities of urban transit systems under climate-induced stress. The proposed
framework provides valuable insights for transit agencies and policymakers seeking to enhance disaster preparedness and ensure the continuity of mobility services during and after extreme weather events. Moreover, the method can be applied to a variety of Canadian contexts for transit agencies, ranging from winter storms to flooding to major disruptions.
|
