RnR-SMART: Resilient smart city evacuation plan based on road network reconfiguration in outbreak response
Jiho Kim, Junwoo Park, Kwangyoung Kim, Mucheol Kim
Abstract
As the frequency of disasters increases worldwide, resilience planning through disaster management has become critical. Disaster managers must make difficult decisions prioritizing various disaster evacuation routes with limited road resources. This study proposes a road network reconfiguration (RnR) framework for disaster evacuation planning. The proposed model proposes a method to reconfigure a road network that can consider various factors based on open-source geographical information systems data. The proposed model first presents a big data processing method for generating an evacuation plan from actual large-scale road network data. This method is adopted for effective routes for large objects. Second, the proposed framework derives routes by disaster risk and is not limited to the minimum route cost, ensuring an optimal safe route according to the degree of risk. As a result, the proposed RnR framework contributes to the resilience of cities by enabling decision-makers and executives in disaster management to design action plans to avoid city risks and conserve human resources.