Evaluating the resilience and recovery of public transit system using big data: Case study from New Jersey.

Analyzing resilience and vulnerability of public transit networks is extremely important in the context of natural disasters as they are essential for evacuation. In this study, the public transit systems in New Jersey based on their vulnerability, resilience, and efficiency during the recovery period following Hurricane Sandy were analyzed. Diverse traffic, infrastructure, events, and web-based sources of Big Data are applied. Due to the sparsity of public transit performance measures for vulnerability, recovery, and resilience, various measures from existing literature were adapted for public transit. Following Hurricane Sandy, the bus transit network of NJ Transit (NJT) recovered much faster than its rail network. This was observed because the road infrastructure recovered much faster as compared to rail and subway networks. Additionally, the most critical link for the NJT buses remained intact during the hurricane whereas rail and subway systems suffered loss of power for driving and signaling. Performance measures such as critical links identification, change in travel time, friability, and resilience triangles for specific bus routes on the NJT bus network were estimated. Transit agencies can use these measures and methodologies in planning and preparing for disasters to study route vulnerability and transit network resilience and standardize performance measures. [ABSTRACT FROM AUTHOR]