Enhancing Road Network Resilience by Considering the Performance Loss and Asset Value

Abstract

In this study, we focus on resilience as the ability of specific infrastructure systems at the regional scale to absorb the shocks of extreme events, such as earthquakes. The occurrence of a disaster such as an earthquake leads to a rapid decrease in infrastructure performance. In the case of road networks, performance might refer to the number of drivers using the road within a certain period of time. The objective of this study is to propose a quantitative evaluation method to analyze road network performance (or performance loss) when natural disasters occur. Furthermore, we use cluster analysis and consider the performance loss and asset value in an attempt to propose a method to determine the critical path that should be prioritized for maintenance. This study aimed at analyzing hazard resilience from the network aspect through a scenario analysis depending on damage recovery after disaster occurrence. This study compared the hazard resilience speed to recover existing performance according to the scenario for damage recovery targeting the selected road network. It was found that the total increase in the utility (e.g., total travel time saved) gradually diminished as the restoration cost increased. Keywords: performance loss; resilience; road infrastructure asset value; road network IntroductionRoad network related assets, such as roads, bridges, and tunnels, are critical infrastructure components that support the economic activities of the surrounding population. If disasters or unexpected situations occur that impact the performance of these networks, there is a high probability that the disruption will diffuse into the surrounding area and can result in the paralysis of the larger network due to the resulting chaos. Because road networks play a pivotal role in evacuation, relief, and rescue efforts over both the short and long term in real disaster situations, it is essential that a disaster prevention plan be developed ahead of time and that the road maintenance be performed regularly to ensure the network will function optimally in times of great need.In many developed countries, including the U.S. and Japan, national and local governments collaborate to establish infrastructure related disaster prevention and restoration plans, to designate certain major roads for both emergency evacuation and transportation, and to train and prepare personnel on how best to respond in order to minimize the damage from disasters [1,2].Increases in the amount of unusual weather due to global warming raises the likelihood of various unexpected situations. The Department for Transport in the UK [3] conducted a study predicting the probability of performance reduction in the traffic sector due to various unexpected situations and the Department of Transport in the U.S. [1] classified the absorption and restoration processes of the traffic system in the event of disasters into several stages, including preparation, impact, response, and restoration, and presented strategies to improve the resilience before and after a disa...

Quantitative Study on the Waterlogging Resilience of Road Transportation System Based on the Validity View of System Functions

“…The numerical values of tm Q at different moments were calculated according to Eq. (5). The results are shown in Table 1.…”

“…In addition, waterlogging resilience has been studied by post-disaster scenario analysis. In the context of postdisaster recovery, disaster resilience has been analyzed from the network perspective [5]. Twumasi-Boakye et al studied the resilience of a regional transportation network and proposed a scene-based traffic modeling and an assessment framework of regional network resilience based on GIS technology, given the damages of bridges by disasters [15].…”

“…However, users' decision can affect their perception of the influences of destructive events on traffic conditions [4]. In addition, scenario analyses based on post-disaster recovery from the network perspective investigate disaster resilience [5], and attach significant attention to the resilience of road transportation systems to earthquake disasters [6]; however, they cover waterlogging resilience insufficiently. Generally, studies on the resilience of road transportation systems mainly focus on three aspects but lack the organic combination of these aspects.…”

Towards Resilient Vital Infrastructure Systems: Challenges, Opportunities, and Future Research Agenda

“…Within the same sector, Román-De La Sancha et al (2019) conducted a study of the accuracy of damage identification models (i.e., fragility curves) for the urban bridges, tunnels, main roads, and metro stations affected by earthquakes to provide a better insight on applicability of these models in seismic vulnerability and resilience assessments. Such damage identification models are extended to damage recovery scenarios to explore the resilience of VIS for a given post-disaster recovery scenario (see Do and Jung, 2018). Enhancing the resilience of the VIS can also be achieved in other ways, e.g., by improving the information flow across organizational levels (from individual to society) and…”

“…Similarly, Majithia (2014), and Giovinazzi et al (2017) conducted studies within the power and telecommunication systems, respectively, in which improvement of the infrastructure's resilience was analysed through sharing knowledge and collaborations among different stakeholders. As another method of increasing infrastructure resilience, risk assessment has been commonly used in the studies conducted by Ruijters and Stoelinga (2016); Hall et al (2016); Do and Jung (2018); Mao et al (2018); Wang et al (2019); and Tsavdaroglou et al (2018). The selected studies also highlight that within the water sector, combining green and grey infrastructures (nature-based solutions) is the most frequently used approach to increase system's resilience (e.g., Hulscher et al, 2014;Augustijn et al, 2014;Demuzere et al, 2014;Borsje et al, 2017;Augustijn et al, 2018;Beery, 2018;Vuik et al, 2019).…”