A simulation-based framework for leveraging shared autonomous vehicles to enhance disaster evacuations in rural regions with a focus on vulnerable populations

Sevim, Alican; Guo, Qianwen; Özgüven, Eren Erman · 2025 · OpenAlex-citations

DOI: 10.1186/s43065-025-00122-6

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Summary

This study addresses the critical gap in disaster evacuation planning for rural regions, specifically focusing on vulnerable populations such as the elderly, individuals with disabilities, and those with limited English proficiency. Rural areas face distinct challenges, including lower income levels, reduced risk perception, and inadequate transportation infrastructure, which traditional evacuation methods relying on state-owned buses and city vans often fail to meet effectively. The authors propose a simulation-based framework to evaluate the integration of Shared Autonomous Vehicles (SAVs) into pre- and post-disaster evacuation strategies, aiming to enhance efficiency and equity for these at-risk groups. The research utilizes Sumter County, Florida, as a case study due to its high concentration of vulnerable residents and status as one of the state’s most transportation-insecure regions. The methodology combines mathematical programming with the open-source traffic simulator SUMO. The simulation models mass evacuations under two conditions: a pre-disaster scenario with fully operational roads and a post-disaster scenario incorporating infrastructure failures and road closures based on FEMA flood hazard maps. Seven scenarios were tested, varying SAV penetration levels from 20% to 100% of the vulnerable population, compared against a baseline using only passenger cars. Each SAV was configured to carry an average of 25 vulnerable individuals, while non-vulnerable residents were assigned to personal vehicles. Bus stop locations were optimized based on population density and accessibility constraints. The results indicate that higher SAV integration significantly improves traffic distribution and reduces congestion. Scenarios with greater SAV presence exhibited lower congestion peaks and more stable traffic flows compared to the baseline. However, mixed traffic environments involving both SAVs and passenger cars showed reduced average speeds due to interactions between vehicle types. In contrast, exclusive SAV usage resulted in higher speeds and more consistent travel patterns. The study also conducted a comparative analysis replacing SAVs with conventional buses under identical conditions to isolate the specific benefits of autonomous capabilities. The findings suggest that SAVs offer a promising solution for rural disaster evacuations by providing flexible routing, increased capacity, and enhanced accessibility for vulnerable populations. The framework demonstrates that SAVs can mitigate the limitations of traditional transit methods, particularly in areas with sparse transportation networks. These insights provide actionable evidence for policymakers and emergency planners to consider SAV technologies in future evacuation strategies, highlighting the potential for more equitable and efficient disaster response systems in rural communities.

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