## 1 Introduction  
Road tunnels, as part of an infrastructure system, are extremely important for the transport of goods and people. To provide the social and economic benefits for which a tunnel is designed and built, it should be kept open to traffic as much as possible. However, the functionality of a road tunnel might be temporarily compromised by a traffic accident or fire occurring within the structure. The consequent non-availability for the passage of traffic flow through the tunnel, which can be caused by the aforementioned incidental event, might also require a great deal of time and effort to normalize the situation. Therefore, the recovery process of the operating conditions of the road tunnel after a disruption of traffic flow, as well as the possible presence of alternative itineraries in the nearby road network, is nowadays becoming a crucial issue for community interests at different levels. Road tunnels, and more commonly a transportation network containing them, that show an adaptive response to a disruptive event are generally described as resilient. However, it is worth pointing out how there is not a shared concept of resilience in different research disciplines, and consequently various definitions can be found in current literature. With specific reference to the case of a transportation system, resilience might, for example, be defined as reported in [PERSON] et al. [1]: _\"the ability of the system to maintain its demonstrated level of service or to restore itself to that level of service in a specified timeframe\"_. Resilience, however, should not be confused with the vulnerability of a transportation system that, instead, represents its susceptibility to a given event without considering the recovery process. Resilience analyses involve the use of certain specific metrics. Since the resilience of a transportation infrastructure is more especially related to its functionality, traffic-related resilience metrics expressed in terms of traffic flow properties should be used. In this respect, a discussion on some available metrics in the field of transportation networks can be found, for example, in [PERSON] and [PERSON] [2], and [PERSON] et al. [3]. However, given that the disruption of functionality of the transportation system caused by an event (e.g., a collision or fire in a tunnel) might significantly increase the travel time of vehicles, the delay time (i.e., the excess time in the transportation facility) can be an appropriate traffic parameter related to resilience. The congestion index due to an event (i.e., the ratio of delay time to acceptable travel time) can also be a measure related to resilience. Resilience may also be treated in terms of the adaptive or restorative capacity. The adaptive capacity is the ability of the transportation system to gradually adapt itself to a disruption. For example, in the case of a twin-tube road tunnel, if a disruption leads to the functionality loss of a one-way tube having two or more lanes, the transportation infrastructure may still recover the functionality by using the remaining undisrupted lane, or in the event of the complete closure of the tube by reorganizing the traffic flow using the adjacent tube for bi-directional traffic (adaptive capacity). If the tunnel operating team restores the disrupted one-way tunnel tube by means of specific activities, this corresponds to the restorative capacity. In addition, the availability of an alternative itinerary in the nearby road network, which might be used when the aforementioned one-way tube is completely blocked due to an incident, may be helpful to represent the resilience of a transportation system (e.g., in terms of the travel time after the disruptive event and the following functionality recovery). The resilience analysis of a transportation system can be conducted through qualitative or quantitative methods. The former approach provides only a descriptive assessment of the resilience of an infrastructure (e.g., low, medium, and high resilience).