Extreme weather events are posing significant challenges to transportation infrastructure networks, both physically and functionally. While previous studies have examined the performance of infrastructure networks against disruptions, rare research integrates segment-level performance metrics, such as traffic volume and speed, to evaluate spatiotemporal operational responses to climate-disruptive events, like hurricanes. This study highlighted multiple traffic segments in transportation networks and investigated their geospatial changes in average traffic volume and median traffic speed before, during, and after hurricanes to quantify segment-level volume and speed resilience. Analyzing highway networks’ traffic and hurricane data from Miami-Dade County, Florida, we revealed four-quadrant performance resilience patterns, including (1) negative volume, positive speed (80 % of the highway networks); (2) both negative (17 %); (3) both positive (0.6 %); and (4) positive volume, negative speed (2.4 %). Volume resilience ranged within −0.04∼0.001 and speed resilience within −0.3∼0.3, indicating volume changes of <4 % of highway capacity and speed changes of <30 % of speed limits during hurricanes. A Bayesian Additive Regression Trees (BART) model identified highway type, lane direction, demographics, and land use as crucial factors influencing resilience. Highways near densely populated neighborhoods with fewer White residents and more diverse land uses exhibited lower volume but higher speed resilience, suggesting racial disparity. These findings offer valuable insights into network design and adaptation planning strategies to enhance transportation resilience and mitigate the impacts of climatic disruptions on network performance.
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号