Disruptions to transportation networks are inevitable. When road networks are not resilient, or in other words, do not recover rapidly from disruptions, unpredictable events can cause significant delays that may be disproportionately greater than the extent of the disruption. Enhancing transportation system resilience can help mitigate the consequences of disruptions; however, required investments are difficult to justify given the low probability of such events. This paper calculates economic implications of unmitigated random disruptions in urban road systems. We modeled delays in transportation networks and demonstrated how resilience can be integrated into macroeconomic modeling via the transportation planning model, REMI TranSight. The model was applied to 10 cities in the United States to forecast the impact of disruptions on gross domestic product (GDP). Different disruption scenarios were modeled and the magnitude of disruption was used to calculate additional delays in transportation networks, which were then integrated into the TranSight model. The results were compared to a baseline case, where economic impact was assumed to be proportional to the magnitude of disruptions. Results show that losses in GDP were far more pronounced in the case scenario as compared to the baseline. The losses tended to be higher in wealthier and more economically productive cities. The economic output tends to rebound one to two years after a disruptive event. We conclude that different topology in transportation networks in different cities requires explicit consideration and quantification of resilience to support investment decisions designed to improve transportation networks in cities.

运输网络的中断是不可避免的。如果道路网络缺乏弹性，或者说无法从中断中快速恢复，那么不可预测的事件可能会导致严重的延迟，而延迟可能远远大于中断的程度。增强运输系统的适应能力可以帮助减轻干扰带来的后果；但是，鉴于此类事件的可能性很小，因此难以证明所需的投资是合理的。本文计算了城市道路系统中不可缓解的随机干扰的经济影响。我们对运输网络中的延误进行了建模，并展示了如何通过运输计划模型REMI TranSight将弹性整合到宏观经济模型中。该模型已应用于美国的10个城市，以预测中断对国内生产总值（GDP）的影响。对不同的中断场景进行了建模，并使用中断的大小来计算运输网络中的其他延迟，然后将这些延迟集成到TranSight模型中。将结果与基准案例进行比较，在基准案例中，经济影响被假定为与中断的程度成比例。结果表明，与基准相比，案例中的GDP损失要明显得多。在较富裕和经济生产性较高的城市，损失往往更高。破坏性事件发生一到两年后，经济产出趋于反弹。