Assessing transport network resilience: empirical insights from real-world data studies

ABSTRACT

Determining the factors that positively and negatively affect the resilience of transport networks provides valuable information that leads to a deeper understanding of the preparedness and response of networks to external disruptions. Over the past few decades, several review papers have explored various interpretations of transport network resilience and its calculation metrics. Nevertheless, only a limited number of these papers have paid attention on the utilisation of empirical data in resilience studies. This paper, through a systematic literature review, contributes to filling this gap. To this end, from a pool of 127 relevant articles, a subset of 53 articles using real-world data was selected. The paper analyses and classifies empirical findings in transport network resilience studies. In particular, it highlights and thoroughly discusses spatial patterns of resilience and relevant influencing factors that positively or negatively affect the resilience attributes of a transport network. Although it is possible to place the empirical results within the theoretical framework proposed by the literature, two main issues on target reference levels arise from the graphical representation of transport network resilience as suggested by the theory. Based on these findings, research gaps are identified and future directions for transport researchers are proposed.

KEYWORDS:

• Transport network resilience
• empirical data
• spatial findings
• influencing factors
• review

Acknowledgments

We are extremely thankful to Prof. Frank Witlox (Ghent University) for the insightful comments and feedback on the original draft and the subsequent revisions.

This paper was developed within the project funded by Next Generation EU – “GRINS – Growing Resilient, INclusive and Sustainable” project (PE0000018), Spoke 7, National Recovery and Resilience Plan (NRRP) – PE9 – Mission 4, Component C2, Intervention 1.3”. The authors acknowledge that the research is also part of the project “GAME: Green, smArt and Mobile urban communitiEs: promotion of inclusive, equitable and integrated social policies for human well-being in cities” funded by the Horizon Europe SEEDS (2022-2023) – University of Bari Aldo Moro.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Fundings

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Notes

1 We acknowledge that both spatial patterns and influencing factors identified are not fully exhaustive in respect to what has been found in the entire transport resilience literature, but they represent a set of interesting results found in the pool of studies we considered.

2 A network is considered to have high infrastructural redundancy when there are numerous available paths that can be chosen to reach a destination.

3 Travel cost refers to the amount of families’ expenditures allocated to transportation (Fernandes et al., 2019), rail operator loss of profits (Janić, 2018) and cost of users passenger in terms of value of time (Janić, 2018; Safitri & Chikaraishi, 2022).