Big Data Analysis of Resilience Between Recurrent and Non-Recurrent Events

The transportation system is particularly vulnerable to disruptive events, while at the same time it is the primary sector for preparedness management and mitigation. The objective of this research is to quantify the changes in vehicle movement during non-recurrent events (Hurricane Irma 2017, Hurricane Michael 2018, and the COVID-19 pandemic in 2020) by comparing with recurrent period for different categories of vehicles, with an emphasis on freight vehicles. This research sought to identify where and when different classes of vehicles were traveling leading up to hurricane landfall and post-storm re-entry. Moreover, this study aims to understand the impact of the pandemic based on different decision made by government and how this decision was affected by the changes in the daily number of cases. The most significant findings showed that the transportation system is very exposed to disruptive events and needs considerable time to recover and adapt. In addition, it was found that freight vehicle transport experience significant changes after the evacuation and the last phases of the pandemic. The less impacted vehicles are those who belong to vehicle category 9 . This category did not have many days with significant changes. On the other hand, the most affected categories were vehicles in category 5 for evacuations and vehicles in categories 5 and 8 for the pandemic. These findings indicate the vehicle category is a parameter that should be taken into consideration in various emergency event management. The guidance of each vehicle group should have a unique design in order to increase management success by the competent authorities.