Data-driven Approach for Assessing Urban Road Network Resilience: Integrating Spatiotemporal Analysis with the Resilience Triangle Concept

Azargoshasbi, Rouzbeh

Data-driven Approach for Assessing Urban Road Network Resilience: Integrating Spatiotemporal Analysis with the Resilience Triangle Concept

dc.contributor.advisor	Kattan, Lina
dc.contributor.author	Azargoshasbi, Rouzbeh
dc.contributor.committeemember	Demissie, Merkebe Getachew
dc.contributor.committeemember	Kutlu, Sule Nur
dc.date	2024-05
dc.date.accessioned	2024-01-19T16:24:04Z
dc.date.available	2024-01-19T16:24:04Z
dc.date.issued	2024-01-18
dc.description.abstract	Urban mobility is constantly challenged by congestion and unpredictable disruptions, making it more crucial than ever to understand and improve the resilience of urban road networks. Growing cities have necessitated reliable and efficient transportation systems, highlighting the importance of a thorough resilience study that analyzes the dynamics and complexities of road networks. Improving resilience is not only about addressing short-term traffic problems; it also aims to ensure the long-term sustainability and adaptability of urban infrastructure. This thesis presents a data-driven approach to investigate the spatiotemporal impact of daily non-recurring disruptions and the resilience of urban road networks. The underlying traffic propagation dynamics and recovery time, vulnerability, and resilience of an urban road network are examined using multi-year observed travel time and incident data. The study develops a statistical method to estimate event occurrence, restoration, and recovery times and formulates a new resilience metric inspired by the resilience triangle concept and complex network theory. The analysis captures the microscopic dynamics of affected road links in detail and allows for an accurate estimation of an incident’s occurrence, restoration, and recovery time. The results indicate that incidents are often detected earlier than reported, but the impact of those incidents remains on the network for a longer period than reported. In addition, areas with low resilience tend to be geographically clustered, often near high-demand regions that have low network densities, indicating inefficiency in the network and low resilience. This study demonstrates that the proposed methodology captures network responses to disruptions accurately and provides valuable insights for transport policy, including the strategic placement of recovery resources, such as police units, during disruptions. The findings of this study have significant implications for the improvement of urban road network resilience.
dc.identifier.citation	Azargoshasbi, R. (2024). Data-driven approach for assessing urban road network resilience: integrating spatiotemporal analysis with the resilience triangle concept (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.
dc.identifier.uri	https://hdl.handle.net/1880/118006
dc.identifier.uri	https://doi.org/10.11575/PRISM/42850
dc.language.iso	en
dc.publisher.faculty	Schulich School of Engineering
dc.publisher.institution	University of Calgary
dc.rights	University of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.
dc.subject	Network resilience
dc.subject	Data-driven approach
dc.subject	Spatiotemporal analysis
dc.subject	Resilience triangle
dc.subject	Complex network theory
dc.subject.classification	Engineering--Civil
dc.title	Data-driven Approach for Assessing Urban Road Network Resilience: Integrating Spatiotemporal Analysis with the Resilience Triangle Concept
dc.type	master thesis
thesis.degree.discipline	Engineering – Civil
thesis.degree.grantor	University of Calgary
thesis.degree.name	Master of Science (MSc)
ucalgary.thesis.accesssetbystudent	I do not require a thesis withhold – my thesis will have open access and can be viewed and downloaded publicly as soon as possible.