Toward climate-resilient freight systems: Measuring regional truck resilience to extreme rainfall via integrated flood demand modeling

This study leverages a comprehensive dataset of over 810,000 heavy-duty trucks to examine the impact of rainfall-induced extreme floods on the resilience of the heavy-duty truck freight system in Beijing, Tianjin, and Hebei Province, China. By integrating the CaMa-Flood model with real-time meteorological data, the truck freight demand model, and the topological road network, a detailed analysis of the effects of the floods on transportation resilience was conducted. Critical road segments were identified, and their timely reopening significantly enhanced the resilience of the truck freight system. This approach addresses the limitations of previous research that often neglected the complex impacts of floods on transportation systems, did not utilize extensive freight demand data, and focused solely on topological resilience analysis. A two-step framework was systematically established to study changes in travel time and network connectivity within the heavy-duty truck freight system. 

The findings highlight the necessity of rapid physical repairs and efficient traffic management to restore post-disaster network service capacity. Identifying critical road segments allows for prioritizing repairs that have the most significant impact on overall system recovery. This study underscores the limitations of relying solely on topological resilience metrics and emphasizes the importance of incorporating functional resilience assessments to comprehensively capture network performance under flood conditions. Future research will focus on two interconnected pathways to advance transportation resilience modeling. First, real-time traffic data from IoT sensors and crowdsourced platforms such as Amap will be integrated to dynamically update resilience metrics during flood events, enabling granular monitoring of network disruptions. Second, adaptive traffic management strategies, including variable toll pricing for alternative routes and AI-driven rerouting algorithms, will be explored to incentivize the rapid redistribution of freight traffic and mitigate congestion hotspots.