Shared Autonomous Vehicles to Facilitate EvacuationÂ
Hurricane evacuation has long been a critical area of study. Traditional methods, which often rely on state-owned buses and city-operated vans, frequently struggle to meet the public's needs during large-scale emergencies. However, rapid advancements in autonomous vehicle (AV) technology have the potential to transform transportation systems, including disaster evacuation strategies, through the integration of Shared Autonomous Vehicles (SAVs). Despite their promise, the application of SAVs for evacuation purposes has received limited attention in public policy discussions.
To improve evacuation efficiency, innovative approaches must be developed to optimize transportation assets and enhance the efficiency of large-scale evacuations. The sharing economy, particularly through shared vehicles and accommodations, offers potential advantages for emergency management personnel during evacuations. This study aims to address existing gaps by evaluating the feasibility of using SAVs in government-led hurricane evacuation efforts.
While previous research has examined the effects of SAVs on travel behavior and demand, there is growing evidence of their ability to complement public transit services and improve efficiency, service quality, and user satisfaction. Examples such as SAV deployment at the Detroit Medical Center Heart Hospital for transporting individuals to medical appointments, and pilot programs at Fort Liberty for access to hospitals and clinics, illustrate promising applications. However, current SAV initiatives have largely focused on urban commuting, with limited attention to the specific challenges of disaster evacuation in high-risk areas.
Key challenges include adapting SAV operations to the specific mobility demands and infrastructure limitations of disaster-prone areas. These challenges encompass factors such as varying population densities, constrained roadway geometries, inconsistent cellular or GPS connectivity, and limited access to charging infrastructure. Additionally, in disaster settings, uncertainties regarding evacuee behavior, road closures, and the dynamic progression of storm paths significantly complicate real-time SAV deployment.
This research seeks to identify the critical design and deployment parameters necessary to ensure the efficacy and reliability of SAV systems under emergency conditions. Specific areas of focus include the optimization of vehicle routing under time-sensitive constraints, dynamic fleet sizing in response to evolving evacuation demands, and multi-zonal scheduling strategies that align with phased evacuation orders issued by local authorities.
To support these efforts, the project will develop and test real-time routing and dispatch algorithms that incorporate live traffic feeds, weather updates, infrastructure status, and priority populations requiring assistance. By modeling a range of demand scenarios and infrastructure disruptions, the project aims to produce a flexible, adaptive deployment framework capable of minimizing total network travel time and congestion.
The effectiveness of the proposed solution will be evaluated using the Simulation of Urban MObility (SUMO) platform, which enables detailed modeling of traffic flow, vehicle interactions, and network-level dynamics. Multiple numerical scenarios representing varying levels of evacuation demand, road network disruptions, and SAV fleet compositions will be constructed. Key performance indicators such as evacuation clearance time, network congestion levels, and fleet utilization rates will be analyzed.
To assess whether the observed benefits are intrinsic to the use of SAVs or attributable to general system-level changes, a comparative analysis will be conducted. This includes substituting SAVs with conventional transit modes, such as buses, under identical conditions to determine the relative efficacy of each mode in terms of speed, reliability, and coverage. The results will help isolate the operational advantages of SAVs, inform future policy design, and support decision-making for integrating emerging mobility technologies into emergency response planning.
The research will involve conducting questionnaires to gather input from communities about the design and operation of Shared Autonomous Vehicles (SAVs) for evacuation scenarios. This feedback will help identify key parameters for deploying SAVs effectively and inform the development of operational strategies tailored to the needs of the affected populations.
The research team from Florida State University will work closely with key community partners, including the Apalachee Regional Planning Council, Big Bend Transit, and the Miami-Dade County Department of Emergency Management. These partners will actively contribute by sharing and evaluating piloted operational strategies, providing insights on their feasibility, effectiveness, and areas for refinement.
The goal of this project is to enhance evacuation planning by developing a streamlined and safe framework for deploying Shared Autonomous Vehicles (SAVs). Through a collaborative research approach, the project aims to overcome regional transportation challenges and ensure that evacuation solutions are efficient, adaptable, and aligned with local needs.
TBD