|
| 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 | Type of interdependent network | Interdependent type between interdependent stations | Resilience measurement indicator | Attack strategy | Major contribution or conclusion |
|
Yang et al.[72]
2014 | Beijing | Bus, Urban rail transit / Yes | Do not define load, and achieve similar effect with the load-capacity model through the binary influence model | - | Normal state, Failure state | There is no direct load redistribution process. It defines the impact of the failure station on the adjacent station by defining the special influence coefficient. | Coupled network constructed by BTN and URTN | Bus station and urban rail transit station are coupled by considering that the upper bound of walking distance is 0.8 km between two stations. | Ratio of station cascading failures | Implementing station state transitions by adjusting the influence strength parameter of binary influence model | The topological characteristics of each sub-network and coupled network are analyzed and the three parameters describing the characteristics of the coupled network are given. Then, the binary influence model is used to simulate the feedback process and cascading failures behavior of the coupled model. |
Su et al.[117]
2014 | Beijing | Bus, Urban rail transit / Yes | Directly define it as station betweenness | Station capacity is proportional to station initial load | Normal state, Overload state | Failure station induces load adjustments of adjacent stations and interdependent stations, and the Gini coefficient proposed by Morris et al.[118] is used to describe the difference in edge load redistribution. | Coupled network constructed by BTN and URTN | It declares that some of bus stations and urban rail transit stations are coupled, but no clear coupled method is declared. | Network efficiency | Attack one single station that has the largest load, Attack one single route of URTN that has the largest load, Attack one single station that is randomly selected from bus transit network, Attack one single station that is randomly selected from URTN | Based on the three attack types: maximum load node attacks, maximum load edge attacks, and random attacks, the cascading failures process of the coupled network is simulated, thus getting that the network efficiency is found to have an unbalanced phase change in a low-capacity network. |
Dong et al.[70]
2014 | Beijing, Shanghai, Hangzhou | Bus / Yes (bus transit transfer network, and bus transit geographical network) | Directly define it as edge weight | Station capacity is proportional to station initial load | (edge) Normal state, Failure state | Redistribution based on the proportion of adjacent edge load | Double layered network coupled by bus transit transfer network and bus transit geographical network | The same numbered stations in the two sub-networks are interdependent with each other, because the interdependent network are coupled by two abstracted network representations of one same bus transit network. | Normalized avalanche size | Attack the edge that has the largest load | Simulation analysis of three urban BTNs shows that the passenger flow of the logical layer (bus transit transfer network) influences the edge load distribution of the physical layer (bus transit geographical network). Additionally, to remove the edge with maximum load may cause physical layer cascade failures, and the normalized avalanche size is negatively related to the edge load tolerance parameter. |
Huang et al.[73]
2015 | Beijing | Bus, Urban rail transit / Yes | Define edge load as edge weight (i.e., average daily 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 | Coupled network constructed by BTN and URTN | No clear coupled method is declared. | Cumulative failure proportion, Failure proportion | Attack one single station that is randomly selected, Attack one single station that has the largest degree or strength | A cascading failures model of weighted network based on the coupled map lattice (CML) is proposed, and it can get the conclusions that the dynamic passenger flow redistribution can significantly improve the PTN resilience under random attacks; the threshold of topological and flow coupled strength in the failure spreading process can be used as an effective strategy for controlling cascading failures. |
Ren et al.[89]
2016 | Shenyang | Bus / Yes (bus transit transfer network, bus transit geographical network, and bus transit route network) | Directly define it as edge weight | Station capacity is proportional to station initial load | (edge) Normal state, Failure state | No clear redistribution proportion is given | Double layered network coupled by bus transit geographical network and bus transit route network, Double layered network coupled by bus transit route network and bus transit transfer network | The same numbered stations in the two sub-networks are interdependent with each other, because the interdependent network are coupled by two abstracted network representations of one same bus transit network. | Relative size of maximum connectivity cluster, Average shortest path length, Network diameter, Network efficiency | Simultaneously attack top ten edges that has the largest loads | To reasonably increase the road capacity can significantly reduce the possibility of cascading failures; to remove certain key edges between stations may reduce the load on BTN. |
Zhang et al.[71]
2016 | Jinan | Bus / Yes (bus transit geographical network, and weighted bus transit network) | Define it based on station strength (for upper-layered network) and betweenness (for lower-layered network); additionally, set exponential type load definition control parameter. | Station capacity is proportional to station initial load | Normal state, Failure state | Redistribution based on the proportion of adjacent station coupled capacity | Double layered network coupled by bus transit geographical network and weighted BTN | The same numbered stations in the two sub-networks are interdependent with each other, because the interdependent network are coupled by two abstracted network representations of one same bus transit network. | Ratio of station cascading failures, the scale of time step cascading failures | Attack one single station that has the largest load | A coupled cascading failures model with interdependent relationship is established, which considers the impacts of adjacent stations to the definitions of the initial station load, the transit capacity of edge, the coupled capacity, and the coupled effect of failure station of lower-layered BTN on the interdependent station of upper-layered BTN. |
Shen et al.[119]
2018 | Chengdu | Bus, Urban rail transit / Yes | Maximum passenger flow of subway route at the peak hour in 2020 predicted by Jin et al.[120] is taken as the initial load of the edges between stations. | Define station capacity based on the designed transit capacity of the route (one-way transit capacity at peak hour for capacity) | Normal state, Failure state | Shortest path redistribution | Coupled network constructed by BTN and URTN | Bus station and urban rail transit station are coupled by considering that the upper bound of distance is 0.5 km between two stations. | Average overload coefficient of failure edge, Network failure degree | Attack one single route of URTN in each simulation experiment, and each route will be conducted a simulation experiment respectively. | It simulates and analyzes the process of spreading, diffusion and cascading failures of blocked passengers under sudden accidents, so that the matching degree of emergency coordination ability between subway routes and bus routes in coupled networks is evaluated, thus providing a basis for effectively coping with the overload of coupled networks. |
|
