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| Author and Study time | Case city | PTN type / Whether multilayered systems are considered | Station initial load definition | Station capacity definition | Station state | Rule of failure load dynamic redistribution | Resilience measurement indicator | Attack strategy | Major contribution or conclusion |
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Ma et al.[99]
2011 | Guiyang | Bus / No | Directly define it as station betweenness | Station capacity is proportional to station initial load | Normal state, Failure state | No load redistribution, the dynamic characteristic is reflected in that the topology changes lead to the capacity of adjacent station becoming smaller, so its load carried by the previous moment may have a relative size updating with the capacity. | Relative size of maximum connectivity cluster, Network efficiency | Attack one single station that has the largest load | With the increase of station load tolerance parameter, the BTN resilience has been significantly improved, i.e., the network capacity can be enhanced by increasing the station designing capacity. |
Zou et al.[100]
2013 | Foshan | Bus / No | Directly define it as station betweenness | Station capacity is proportional to station initial load | Normal state, Failure state | Shortest path redistribution calculated by Dijstra algorithm | Relative size of maximum connectivity cluster, Network efficiency | Attack one single station that has the largest load | By comparing the similarities and differences between the static resilience and the dynamic resilience, the stations with more important and extensive impact are identified. |
Du et al.[101]
2015 | Lanzhou | Bus / No | Station weight | Define it as a nonlinear function, i.e., a chaotic Logistics map | Normal state, Failure state | No load redistribution, the adjacent stations are affected by the failure station load, which is characterized by a coupled map lattice function, i.e., station status updates dynamically. | Ratio of station cascading failures | Attack one single station that has the largest saturability, Attack one single station that has the largest degree, Attack one single station that is randomly selected | By conducting parameter simulation of the coupled map lattice based cascading failures for the complex BTN with multi-edges, it found that the larger the coupled strength and the external disturbance value of the network are, the easier the cascading failures will be, and there is a clear threshold; the failure caused by the stations with the largest degree is most likely to trigger cascading failures. |
Zhang et al.[69]
2016 | Jinan | Bus / No | Define it based on station strength; additionally, set exponential type load definition control parameters | Station capacity is proportional to station initial load | Normal state, Failure state | Redistribution based on the proportion of adjacent station capacity | Ratio of station cascading failures | Attack one single station that has the largest load, Attack one single station that has the second largest load, Attack one single station that has the fifteenth largest load | The dynamic resilience model for weighted BTN under single station happening emergency is established, so as to getting that the strength of failure station, the station load tolerance parameter, and the station load distribution control parameter all have important influences on the dynamic resilience. |
He et al.[102]
2016 | Beijing | Bus / No | Actual bus card passenger flow data fitting | Station capacity is proportional to station initial load | Normal state, Failure state | Transfer route-based optimal path navigation strategy, i.e., the shortest path redistribution | Structural integrity, Functional integrity | Attack one single station that has the largest load | A path navigation strategy describing the passenger flow spreading of BTN is proposed, making the station load definition and the actual traffic value be basically the same. |
Zhang et al.[32]
2018 | Jinan | Bus / No | Define it based on station strength and considering the impact of the adjacent station; additionally, set exponential type load definition control parameters | Station capacity is proportional to station initial load | Normal state, Failure state | User equilibrium redistribution based on edge congestion effect (BPR road impedance function[103]) | Global ratio of cascading failures in a time step, Local ratio of cascading failures in a time step | Attack one single station that has the largest load | By balancing the description accuracy and computational efficiency, a cascading failures model of weighted BTN considering congestion effect and user equilibrium evacuation is established. Additionally, based on simulation experiments, the dynamic characteristics of the three failure load redistribution patterns are compared, so that an effective control and optimization direction for BTN resilience is obtained. |
Huang et al.[104]
2018 | Shanghai | Urban rail transit station / No | Define it as the passenger flow per unit area based on Fruin[105] service level | The summation of the maximum service capacity and the maximum queuing capacity of the facility nodes in a unit area | Normal state, Failure state | User equilibrium redistribution based on service chain congestion effect (BPR road impedance function) | Maximum capacity of the entire station | Attack one single facility node that has the largest in-degree | Based on the analysis of the passenger flow service chain inside the urban rail transit station, the station ticket gates, escalators, platforms and other facilities are abstracted into an facility associated network, so that a load capacity calculation method for urban rail traffic station considering cascading failures is established. |
Sun et al.[106]
2018 | Beijing | Urban rail transit / No | Station weight, i.e., Define it as the passenger flow | Define it as a nonlinear function, i.e., a chaotic Logistics map | Normal state, Failure state | Redistribution based on the proportion of connected edge weights between the failure station and its adjacent stations | Cumulative global ratio of cascading failures in a time step, Global ratio of cascading failures in a time step | Attack one single station that has the largest strength, Attack one single station that has the largest degree, Attack one single station that has the largest betweenness | Based on the attack simulation experiment, it can get that the damaged threshold of loop route is much smaller than a straight route. Additionally, observing the attacked loop route, the discrete degree of peak time and all station failure time are higher than straight route, meaning that controlling this failure is quite difficult. |
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