## 1 Introduction  
Connected vehicles are equipped with devices that enable communication within and externally with other vehicles, infrastructure, and networks. This connectivity encompasses Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communications, aiming to enhance safety, mobility, and environmental sustainability [1]. The U.S. Department of Transportation's Vehicle-Infrastructure Integration (VII) program sought to improve roadway safety and mobility by enabling real-time data exchange between vehicles and infrastructure using wireless communications [1]. Connected vehicle applications are broadly categorized into safety, mobility, and environmental domains. Safety applications include systems like forward collision warnings and blind spot detection, which alert drivers to potential hazards [2]. Mobility applications leverage real-time data to optimize traffic flow and reduce congestion. Environmental applications inform drivers about eco-friendly choices, such as optimal driving speeds to reduce emissions [3]. The integration of connected vehicle technologies holds the promise of transforming transportation systems by enhancing safety, improving traffic efficiency, and reducing environmental impacts [4]. In the context of disaster management, connected vehicle data can be instrumental in predicting shelter demand and optimizing evacuation routes. By analyzing real-time vehicle trajectories, authorities can make informed decisions to ensure public safety during emergencies [5]. The increasing frequency and intensity of natural disasters, particularly hurricanes driven by climate change, necessitate reconsidering disaster response strategies. The global warming signal has been evident since the 1960s [6; 7], with even a modest rise in global temperatures leading to a substantial 25-30% increase in the regional and global frequency of Category 4-5 hurricanes [8]. Furthermore, some associations between the rising ocean temperatures and the frequency of hurricanes have been reported: historical data from the Atlantic region indicate a rising frequency of hurricanes, with trends suggesting a linear increase over time [9]. The provision of shelters for displaced populations due to natural disasters is one of the most critical components of disaster preparedness and response [10; 11]. In planning and managing emergency shelters, accurately predicting the demand for these facilities during disasters is one of the biggest challenges. Depending on the magnitude and location of the disaster, the size and composition (e.g., proportions of vulnerable populations) of the displaced people can vary significantly and therefore there is a need to develop efficient data-driven methods for predicting demand for such facilities. Traditionally, congregate shelters such as schools, community centers, and sports centers have been used to house large numbers of evacuees [12]; however, they have been challenged lately in response to growing uncertainties associated with disasters [13]. These traditional congregate shelters pose significant challenges regarding capacity management, logistical coordination, and health risks, especially during pandemics such as the COVID-19 pandemic. Their limitations underscore the need for alternative solutions [14]. When a geophysical hazard coincides with an ongoing pandemic, the capacities of traditional shelters should be drastically reduced due to social distancing requirements. To minimize the virus exposure risk and maintain social distancing requirements, alternative non-congregate shelters, such as hotels/motels, renovated facilities, or campgrounds, may need to be considered. A key challenge with respect to disaster management, however, is that, while non-congregate shelters are smaller in capacity, they should be larger in number and more geographically dispersed. The COVID-19 pandemic introduced unique challenges with respect to disaster management during co-occurring hurricanes and pandemics.