## 2 Literature Review
[3] provided a literature review of different metrics for the resilience assessment. Discussions concerning uncertainties, interdependencies, and validations due to a general scarcity of data are also made. Additionally, they stressed that the functionality of the transportation system can be improved by increasing the network connectivity (e.g., a greater number of interconnections between two nodes means a higher redundancy of the transportation network). [PERSON] et al. [12] proposed a methodology able to demonstrate the effectiveness of re-routing as a real-time traffic management measure on the resilience of an urban road network when a link is closed due to an incident. They found that when 15% of the vehicles are re-routed, gridlock is avoided, thus enhancing the resilience of the network. [PERSON] et al. [13] dealt with transportation network redundancy, which is another important concept in characterizing resilience. In particular, they introduced two measures (i.e., travel alternative diversity, and network spare capacity) to characterize the redundancy of a transportation system in the case of a disruptive event, such as an earthquake or a severe traffic accident. By performing two numerical examples, the authors demonstrated the necessity both of introducing new routes and increasing the capacity of existing links to improve network redundancy. [PERSON] and [PERSON] [14] focused both on the ability of a network to sustain the consequences of a disruption (i.e., resistance) and quickly recover its performance (i.e., rapidity). By modeling both these concepts to characterize the resilience and to identify an optimal choice, they showed for a specific case how some recovery strategies can reduce the disruption consequences. [PERSON] et al. [15] developed a method to optimize traffic signal settings in an urban road network in order to improve the resilience during the occurrence of disruptive events. Several blockage scenarios involving various combinations of capacity reduction and duration of the blockage were simulated. The optimization of the traffic signals was found to minimize both network travel time and carbon dioxide emissions. [PERSON] et al. [16] developed a stochastic simulation model in order to quantitatively assess the functionality loss and resilience of a tunnel subjected to random events (e.g., traffic accidents or fires) or planned events (e.g., operation and maintenance of the tunnel). A functionality metric dependent on traffic capacity loss and its duration was used. [PERSON] [17] set up a genetic algorithm for optimizing a highway network after a natural disaster or accident that led to the failure of a certain number of road sections. The resilience metrics used were expressed in terms of both the shortest time for road repair and the least loss of road network performance. The functionality of the road network was assumed to be restored by means of external recovery measures, such as the intervention of engineering repair teams. [PERSON] et al. [18] evaluated the functional changes in the organization of a transportation network concerning the transition to one-way roads vs two-way traffic. PIARC [19] reported the state-of-the-art on road tunnel resilience with applications of some case studies. The above chronological literature review, even if it is not exhaustive due to a great number of studies on resilience in different disciplines of research, is sufficient to show how many scientific articles focused prevalently on both different metrics to evaluate transportation network resilience and the concepts for its characterization in the event of disruptions. They also consider different recovery strategies. However, the resilience of road tunnels, as a part of a transportation network, appears to have been investigated to a lesser degree. Moreover, the aforementioned studies have been carried out in countries where the transportation infrastructure geometry, the traffic characteristics, and the driving behavior differ from those in Italy.