Dynamic Partitioning of Transportation Network Using Evolutionary Spectral Clustering

Alam, Pamela Al; Hamad, Denis; Constantin, Joseph; Constantin, Ibtissam; Zaatar, Y.

doi:10.1007/978-3-030-45183-7_13

Cited by 2 publications

(7 citation statements)

References 12 publications

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“…(5) From the perspective of computational time complexity, the computational time complexity needed to carry out an iteration in this paper is similar to that in [29,30], but better than that in [27,28]. However, the number of iterations converging to the optimal solution in this paper will be better than those in [29,30]. is is because this paper takes the initial partition result as the initial solution of the static partition and carries out iterative search on this basis.…”

Section: Methods Comparisonmentioning

confidence: 91%

“…is paper, together with literature [27][28][29][30], believes that there is a macroscopic basic diagram (MFD) in road network, which plays an important role in dynamic traffic management, traffic signal control, and urban traffic congestion mitigation. However, the largescale road network is usually a heterogeneous network, and the heterogeneity has a strong influence on the shape of MFD and the mode of the system in MFD.…”

Section: Methods Comparisonmentioning

confidence: 99%

“…en, the modularized and optimized fast network partition method is used as the criterion to identify the isomorphic subnetworks in the large-scale urban road network. Literature [29] proposed an evolutionary spectral clustering algorithm to divide time-varying heterogeneous networks into connected homogeneous regions. e sparse matrix is obtained by calculating the similarity, which simplifies the complexity of the algorithm.…”

Section: Methods Comparisonmentioning

confidence: 99%

“…From the calculation formula of similarity index, this index can describe the homogeneity of traffic flow density more, but the ability to describe the homogeneity of road structure is a little insufficient. Literature [29] only uses the average speed of a section as a clustering index, and the average speed of a section can only describe the traffic flow density of a section indirectly, which is not intuitive. At the same time, there is also a lack of relevant traffic parameters that can reflect the description of the homogeneity on the road structure.…”

Section: Methods Comparisonmentioning

confidence: 99%

“…Literature [27] Literature [28] Literature [29] Literature [30] is paper n for the scale of the road network; t is the number of partitions; k is the number of iterations. e "cumulative number of iterations" is the sum of the numbers of iterations for each partition.…”

Section: Namementioning

confidence: 99%

See 4 more Smart Citations

Subdivision of Urban Traffic Area Based on the Combination of Static Zoning and Dynamic Zoning

Luo

Zhang

2021

Discrete Dynamics in Nature and Society

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In this paper, the traffic area of subzone division in urban road network is studied and a subzone division method based on the combination of static partition and dynamic partition is proposed. The static partition is carried out for the road network when the traffic flow is in a noncongested state, so as to provide the decision-making basis for the traffic green wave signal control strategy. At the same time, aiming at the road network when the traffic flow is congested, the dynamic partition is carried out on the basis of static partition to provide the decision-making basis for the traffic maximum flow signal control strategy. In view of the fact that it is difficult to determine the clustering center point during the initial division, this method proposes to determine the clustering center point according to the value of nodes of betweenness centrality. In order to solve the problem that it is difficult to collect traffic data, a method for estimating traffic flow density is proposed. In order to solve the problem of normalization of different probability distribution among various parameters, Mahalanobis distance is used as the fusion index of subzone division. Model verification shows that the method is feasible and effective.

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Section: Methods Comparisonmentioning

confidence: 91%

Section: Methods Comparisonmentioning

confidence: 99%

Section: Methods Comparisonmentioning

confidence: 99%

Section: Methods Comparisonmentioning

confidence: 99%

Section: Namementioning

confidence: 99%

See 3 more Smart Citations

Subdivision of Urban Traffic Area Based on the Combination of Static Zoning and Dynamic Zoning

Luo

Zhang

2021

Discrete Dynamics in Nature and Society

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Partitioning of Transportation Networks by Efficient Evolutionary Clustering and Density Peaks

Alam

Constantin

et al. 2022

Algorithms

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Road traffic congestion has became a major problem in most countries because it affects sustainable mobility. Partitioning a transport network into homogeneous areas can be very useful for monitoring traffic as congestion is spatially correlated in adjacent roads, and it propagates at different speeds as a function of time. Spectral clustering has been successfully applied for the partitioning of transportation networks based on the spatial characteristics of congestion at a specific time. However, this type of classification is not suitable for data that change over time. Evolutionary spectral clustering represents a state-of-the-art algorithm for grouping objects evolving over time. However, the disadvantages of this algorithm are the cubic time complexity and the high memory demand, which make it insufficient to handle a large number of data sets. In this paper, we propose an efficient evolutionary spectral clustering algorithm that solves the drawbacks of evolutionary spectral clustering by reducing the size of the eigenvalue problem. This algorithm is applied in a dynamic environment to partition a transportation network into connected homogeneous regions that evolve with time. The number of clusters is selected automatically by using a density peak algorithm adopted for the classification of traffic congestion based on the sparse snake similarity matrix. Experiments on the real network of Amsterdam city demonstrate the superiority of the proposed algorithm in robustness and effectiveness.

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Dynamic Partitioning of Transportation Network Using Evolutionary Spectral Clustering

Cited by 2 publications

References 12 publications

Subdivision of Urban Traffic Area Based on the Combination of Static Zoning and Dynamic Zoning

Subdivision of Urban Traffic Area Based on the Combination of Static Zoning and Dynamic Zoning

Partitioning of Transportation Networks by Efficient Evolutionary Clustering and Density Peaks

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