Static and dynamic resilience assessment for sustainable urban transportation systems: A case study of Xi 'an, China

Zhou, Ruiyu; Chen, Hengrui; Lau, Albert

doi:10.1016/j.jclepro.2022.133237

Cited by 18 publications

(13 citation statements)

References 32 publications

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“…Shojaat et al [20] determined the speed threshold as the boundary between the fuid and congested trafc by analysing the speed and fow time series. Given this, from the perspective of road network resilience, we used the previous research results to determine the critical threshold of trafc congestion difusion by using the percolation theory to determine the critical speed of the road [21,22].…”

Section: Methodsmentioning

confidence: 99%

“…As mentioned before, from the perspective of road network resilience, we used the previous research results to determine the critical threshold of trafc congestion difusion by using the percolation theory to determine the critical speed of the road [21,22]. Te critical speed of reserved road was approximately 30 km/h.…”

Section: Calculation Of Reservation Road Orvmentioning

confidence: 99%

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Optimal Reservation Volume of Urban Roads Based on Travel Reservation Strategy

Zhou,

Chen,

Chen

2024

Journal of Advanced Transportation

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Improving the spatial-temporal balance between the supply and demand of urban transportation and alleviating traffic congestion are important ways to build sustainable cities. The travel reservation strategy (TRS) is more flexible and refined than traditional traffic demand management methods. This study aims to determine the optimal reservation volume (ORV) for urban roads and verify the effectiveness of the TRS. First, we employed the sustained flow index to estimate the ORV from the degree of trade-off between the road breakdown probability and capacity. Then, a bilevel programming model based on ORV constraints was established to analyse the effectiveness of the TRS. The results indicated that the ORV range is 0.79–0.89 times the road capacity. The TRS can achieve the best steady benefit when the demand for reservation travel reaches at least 40%. Selecting the most congested critical roads in the network to implement TRS is more effective than on a large area. The driver default behavior will increase the V/C ratios and travel costs of all roads in the network. It has been proven that the reservation transportation mode will promote the spatial-temporal balance between supply and demand to alleviate traffic congestion.

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Section: Methodsmentioning

confidence: 99%

Section: Calculation Of Reservation Road Orvmentioning

confidence: 99%

Optimal Reservation Volume of Urban Roads Based on Travel Reservation Strategy

Zhou,

Chen,

Chen

2024

Journal of Advanced Transportation

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“…Hossain et al [ 40 ] identified key factors that enhance the resilience of port infrastructure systems through BNs. Chen et al [ 41 ] devised a comprehensive Bayesian network model that amalgamates social, economic, organizational, and technological factors to evaluate the static resilience of urban transportation systems.…”

Section: Literature Reviewmentioning

confidence: 99%

Integrating FRAM and BN for enhanced resilience evaluation in construction emergency response: A scaffold collapse case study

Guo,

She,

et al. 2024

Heliyon

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“…Cretney (2014: 630) identifies the same two aspects of resilience in a review that includes both natural and social science disciplines. Building on the identification of these two different aspects of resilience, the most recent contributions draw a distinction between static and dynamic resilience (Simonovic & Arunkumar 2016;Deloukas & Apostolopoulou 2017;Chen et al 2022). Static resilience is when a unit manages to fully recover and preserve its form and functioning in the wake of disruptive perturbations, while dynamic resilience is when the unit adjusts its form and functioning to the new and unforeseen circumstances.…”

Section: From Resilience and Agility To Robustnessmentioning

confidence: 99%

Robust Governance in Turbulent Times

Ansell,

Sørensen,

Torfing

et al. 2024

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This Element aims to build, promote, and consolidate a new social science research agenda by defining and exploring the concepts of turbulence and robustness, and subsequently demonstrating the need for robust governance in turbulent times. Turbulence refers to the unpredictable dynamics that public governance is currently facing in the wake of the financial crisis, the refugee crisis, the COVID-19 pandemic, the inflation crisis etc. The heightened societal turbulence calls for robust governance aiming to maintain core functions, goals and values by means of flexibly adapting and proactively innovating the modus operandi of the public sector. This Element identifies a broad repertoire of robustness strategies that public governors may use and combine to respond robustly to turbulence. This title is also available as Open Access on Cambridge Core.

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Static and dynamic resilience assessment for sustainable urban transportation systems: A case study of Xi 'an, China

Cited by 18 publications

References 32 publications

Optimal Reservation Volume of Urban Roads Based on Travel Reservation Strategy

Optimal Reservation Volume of Urban Roads Based on Travel Reservation Strategy

Integrating FRAM and BN for enhanced resilience evaluation in construction emergency response: A scaffold collapse case study

Robust Governance in Turbulent Times

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