The DOI matches its Crossref record; 86 of the 86 references it cites were found in a registry or an index.
Urban Transportation Networks Resilience: Indicators, Disturbances, and Assessment Methods
Open accessAbstract
Due to a surge in the frequency and intensity of disruptive events, such as natural disasters, the Covid-19 pandemic, and intentional attacks, the concept of resilience has attracted increased attention in recent years. Many scholars have focused on transportation network resilience because of its importance in society's well-being and recovery efforts after disturbances. Existing studies have suggested various definitions, indicators, and methods for assessing the resilience of transportation networks. This variation is due to differences in the nature, scale, and impact of disturbances. This systematic literature review presents resilience assessment methods for transportation networks, indicators, and disturbance categories. A new representation is suggested for the relationships between performance, time, and resilience, emphasizing other network characteristics and their association with resilience. Resilience indicators are categorized, and disturbance categories are analyzed. Approaches are grouped based on their methodologies and presenting their strengths and limitations. This paper directs future studies toward investigating emerging threats, including climate change, pandemics, cybersecurity, failure propagation, and the impacts of new technologies and paradigms on urban transportation resilience. Additionally, it highlights the benefits of identifying a reference metric. Finally, this paper promotes resilience-based thinking to address challenges facing cities worldwide as a cornerstone for creating lasting sustainable development.
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Cites
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A review of definitions and measures of system resilience
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A review of urban transportation network design problems
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Metadata
- Authors
- Serdar, M. Z., Koç, M., & Al-Ghamdi, S. G.
- Venue
- Sustainable Cities and Society
- Publisher
- Elsevier BV
- Published
- 2022-01
- Volume
- 76
- Pages
- 103452
- ISSN
- 2210-6707 (ISSN-L)
- OpenAlex
- W3206186094
- Cited by
- 292
- References
- 86
- FWCI
- 17.37
- Type
- journal article
- Language
- en
- Open access
- hybrid
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.