Assessing the Vulnerability of Transportation Network System

The transportation-combined economic model (TCEM) is an analytical tool for investigating the impact of disasters that cause the transportation system to collapse and adversely affect regional economies. While economic models used in TCEM have been steadily developed over the past decade, the transportation module remains at a basic level. The purpose of this study is to develop the transportation module in TCEM. While the model utilizes historical or hypothetical disaster scenarios, we do not know whether a disaster will happen before it actually happens. Therefore, it is necessary to focus on the transportation system rather than on uncertain hazards, and then analyze the comprehensive transportation system vulnerability. This vulnerability means the degree of degradation in the functionality of a system when particular assets collapse. If there are facilities that have a catastrophic impact on the overall system, their vulnerability can be reduced by physically strengthening the facility or installing alternative facilities. A case study of the transportation system vulnerability assessment of the binational highway network between the United States and Canada is provided. The modified betweenness centrality score and the reduced local efficiency were combined to identify critical transportation assets in the connectivity of this binational highway network. Simulations of single-target attacks and continuous-targeted attacks were conducted to identify locations with high vulnerability. Reduced system functionality affects interregional trade. To model this relationship, a traffic assignment model that employs a user-equilibrium algorithm is needed. In the analysis based on any scenario, only a few traffic assignment processes are required to analyze the economic damage by region and industry. However, in the context of a comprehensive analysis centered on vulnerability, it is necessary to assign traffic flows hundreds of times in order to analyze the expected damages caused by the collapse of facilities with high vulnerability. This raises the need for a more efficient user-equilibrium algorithm. Insights for developing this new algorithm were proposed by solving three major problems of the Frank-Wolfe algorithm. A theoretical decision rule of the minimum level of lambda was provided. Level of lambda simulations were provided to verify the proposed rule. Four types of decreasing lambda functions with various initial lambda levels were also conducted with three parameters: total travel cost, total link volume, and convergence ratio. These simulation results provided valuable insights for improving the efficiency of the FW algorithm.