Resilience model and recovery strategy of transportation network based on travel OD-grid analysis

Pan, Xing; Dang, Yuheng; Wang, Huixiong; Hong, Dongpao; Li, Yuehong; Deng, Hongxu

doi:10.1016/j.ress.2022.108483

Cited by 56 publications

(12 citation statements)

References 48 publications

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“…Absorption [ 21 , 32 , 33 ], survivability [ 22 , 27 ], mitigation [ 23 ], degradation [ 24 ], damage propagation [ 25 ], response [ 26 , 28 , 29 ], withstand [ 30 ], disturbance [ 31 ], loss [ 34 ]…”

Section: Literature Reviewmentioning

confidence: 99%

Monitoring the elasticity of travel demand with respect to changes in the transport network for better policy decisions during disasters

Safitri

Chikaraishi

2023

PLoS ONE

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When a disaster occurs, disaster management goes through a number of phases, namely normal, emergency response, adaptation, and recovery. Being able to identify the transition between these phases would be useful for policymakers, for example, in order to shift their focus from meeting the travel needs of affected people during the emergency response phase, to meeting travel needs for adaptation and recovery activities. This study proposes a data-driven method which may be useful for assessing phase transitions for transport management during a disaster. Specifically, we argue that changes in elasticities of travel demand with respect to changes in the transport network can be a useful indicator of phase transition, since they depict changes in consumers’ tastes, i.e., changes in the degree of travel necessity during disaster. Two hypotheses are formulated to investigate the changes in elasticity during a disaster: 1) the elasticity of travel demand is more elastic soon after a disaster as travel becomes a luxury good, and 2) it becomes less elastic afterwards as travel goes back to being a necessity good. To empirically confirm the hypotheses, we develop a multilevel log-log linear model, where the transport network service level information varying over time during a disaster is used as an explanatory variable, and tested mobile phone location and transport network data captured during the heavy rain disaster in Japan in July 2018. We also utilized a change point detection algorithm to identify a structural change that occurred in these elasticities. We confirm that our empirical results support our hypotheses, i.e., in the affected areas, the elasticity was more elastic soon after the disaster, while the elasticity tended to go back to normal around one month later. These results suggest that the proposed method can be useful to judge the phase transition for disaster management.

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Section: Literature Reviewmentioning

confidence: 99%

Monitoring the elasticity of travel demand with respect to changes in the transport network for better policy decisions during disasters

Safitri

Chikaraishi

2023

PLoS ONE

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“…In the context of risk management, resilience is a measure of how much the system keeps moving users with an acceptable level of service in the presence of external events, such as disasters [33,34,35].…”

Section: Letmentioning

confidence: 99%

Network Design Pro Blem for Risk Reduction in Transport System: A Models Specification

Vitetta¹

2022

Int. J. TDI

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With the occurrence of natural or anthropogenic events, which can cause damage to people, delayed in time, adequate actions must be implemented to evacuate the population from the areas at risk. In this context, the transport supply system must be adequately designed to facilitate rapid evacuation.This paper presents the design methodologies of transport networks in the presence of disasters. The design variables considered concern the direction of travel of the links and the regulation strategies to be adopted in the junctions. The objective function considers risk minimization in terms of user exposure. In the problem, the main constraint considered concerns the users' behaviour. In fact, the configuration of the supply system can be optimized but it is necessary to consider that users adopt choice strategies that tend to minimize their disutility. Therefore, the best possible configuration must be found for all users (system optimum), considering that the choices of individual users are with maximum individual utility (user choice).The paper reports the main characteristics that a decision support system should have in terms of: general framework, model and resolution procedures. The decision support system can be used by the decisions that have to design the transport network through preventive actions or in real time.

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“…In contrast, the traffic flow in the other direction is small, resulting in idle road resources, waste of road resources and low traffic capacity. The network-based variable lane control method is analyzed theoretically in the existing research on variable lane (Pan et al , 2022). By establishing a bilevel programming model (Meng and Khoo, 2008) based on the optimal system performance, the corresponding solution method is designed to calculate the attributes of variable lane control nodes (Wang et al , 2013). The main objects of variable lane management include road channelization, information control scheme and social vehicles.…”

Section: Strategies Of Enhancing Resilience Under Various Scenariosmentioning

confidence: 99%

Resilience concepts in integrated urban transport: a comprehensive review on multi-mode framework

Wang

Gao

et al. 2022

SRT

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Purpose Resilience concepts in integrated urban transport refer to the performance of dealing with external shock and the ability to continue to provide transportation services of all modes. A robust transportation resilience is a goal in pursuing transportation sustainability. Under this specified context, while before the perturbations, robustness refers to the degree of the system’s capability of functioning according to its design specifications on integrated modes and routes, redundancy is the degree of duplication of traffic routes and alternative modes to maintain persistency of service in case of perturbations. While after the perturbations, resourcefulness refers to the capacity to identify operational problems in the system, prioritize interventions and mobilize necessary material/ human resources to recover all the routes and modes, rapidity is the speed of complete recovery of all modes and traffic routes in the urban area. These “4R” are the most critical components of urban integrated resilience. Design/methodology/approach The trends of transportation resilience's connotation, metrics and strategies are summarized from the literature. A framework is introduced on both qualitative characteristics and quantitative metrics of transportation resilience. Using both model-based and mode-free methodologies that measure resilience in attributes, topology and system performance provides a benchmark for evaluating the mechanism of resilience changes during the perturbation. Correspondingly, different pre-perturbation and post-perturbation strategies for enhancing resilience under multi-mode scenarios are reviewed and summarized. Findings Cyber-physic transportation system (CPS) is a more targeted solution to resilience issues in transportation. A well-designed CPS can be applied to improve transport resilience facing different perturbations. The CPS ensures the independence and integrity of every child element within each functional zone while reacting rapidly. Originality/value This paper provides a more comprehensive understanding of transportation resilience in terms of integrated urban transport. The fundamental characteristics and strategies for resilience are summarized and elaborated. As little research has shed light on the resilience concepts in integrated urban transport, the findings from this paper point out the development trend of a resilient transportation system for digital and data-driven management.

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Resilience model and recovery strategy of transportation network based on travel OD-grid analysis

Cited by 56 publications

References 48 publications

Monitoring the elasticity of travel demand with respect to changes in the transport network for better policy decisions during disasters

Monitoring the elasticity of travel demand with respect to changes in the transport network for better policy decisions during disasters

Network Design Pro Blem for Risk Reduction in Transport System: A Models Specification

Resilience concepts in integrated urban transport: a comprehensive review on multi-mode framework

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