Multiscale identification of emergent and future conditions along corridors of transportation networks

Transportation agencies are challenged with managing large-scale networks of roads, spanning geographic areas diverse in terms of jurisdictions, topography, demographics, economy, organizations, and others. Risk management, asset management, and resource allocation must be approached from a holistic perspective without compromising specific regional needs. Agencies collect a large amount of data, the utilization of which should be transparent and consistent with their stated aims. The innovation of this paper is a corridor trace analysis, a method for identifying anomalies of hazard intensity, exposure, and vulnerability along many thousands of kilometers of a transportation network by integrating key road characteristic and performance metrics to straight-line diagrams of corridor sections. Road segments under stress are identified by searching for one or more characteristics that are outliers with respect to the contextual data. The paper includes demonstrations of this method for big-data integration on a real-world system, focusing on how the method is useful to shift among geographic scales. The demonstrations suggest the efficacy of the approach to sustain the efficient, reliable, and safe movement of passengers and freight.