Research on Road Network Partitioning Considering the Coupling of Network Connectivity and Traffic Attributes
The urban road network is a large and complex system characterized by significant heterogeneity arising from different spatial structures and traffic demands. To facilitate effective management and control, it is necessary to partition the road network into homogeneous sub-areas. In this regard, we...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-08-01
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| Series: | ISPRS International Journal of Geo-Information |
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| Online Access: | https://www.mdpi.com/2220-9964/12/8/327 |
| _version_ | 1797584461808795648 |
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| author | Yingying Ma Minglang Xu Xiaoran Qin Ying Zeng Lingyu Zeng |
| author_facet | Yingying Ma Minglang Xu Xiaoran Qin Ying Zeng Lingyu Zeng |
| author_sort | Yingying Ma |
| collection | DOAJ |
| description | The urban road network is a large and complex system characterized by significant heterogeneity arising from different spatial structures and traffic demands. To facilitate effective management and control, it is necessary to partition the road network into homogeneous sub-areas. In this regard, we aim to propose a hybrid method for partitioning sub-areas with intra-area homogeneity, inter-area heterogeneity, and similar sizes, called CSDRA. It is specifically designed for bidirectional road networks with segment weights that encompass traffic flow, speed, or roadside facility evaluation. Based on community detection and spectral clustering, this proposed method comprises four main modules: initial partition, partitioning of large sub-areas, reassignment of small sub-areas, and boundary adjustment. In the preliminary partitioning work, we also design a road network reconstruction method which further helps to enhance the intra-area homogeneity and inter-area heterogeneity of partitioning results. Furthermore, to align with the requirement for comparable work units in practical traffic management and control, we control the similarity in the size of sub-areas by enforcing upper and lower bound constraints on the size of the sub-areas. We verify the outperformance of the proposed method by an experiment on the partitioning of an urban road network in Guangzhou, China, where we employ sidewalk barrier-free score data as segment weights. The results demonstrate the effectiveness of both the road network reconstruction method and the CSDRA proposed in this paper, as they significantly improve the partitioning outcomes compared with other methods using different evaluation indicators corresponding to the partitioning objectives. Finally, we investigate the influence of constraint parameters on the evaluation indicator. Our findings indicate that appropriately configuring these constraint parameters can effectively minimize sub-region size variations while having minimal impact on other aspects. |
| first_indexed | 2024-03-10T23:53:02Z |
| format | Article |
| id | doaj.art-110d0c0b952a424e9463c925d2364881 |
| institution | Directory Open Access Journal |
| issn | 2220-9964 |
| language | English |
| last_indexed | 2024-03-10T23:53:02Z |
| publishDate | 2023-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | ISPRS International Journal of Geo-Information |
| spelling | doaj.art-110d0c0b952a424e9463c925d23648812023-11-19T01:23:57ZengMDPI AGISPRS International Journal of Geo-Information2220-99642023-08-0112832710.3390/ijgi12080327Research on Road Network Partitioning Considering the Coupling of Network Connectivity and Traffic AttributesYingying Ma0Minglang Xu1Xiaoran Qin2Ying Zeng3Lingyu Zeng4Department of Transportation Engineering, South China University of Technology, 381 Wushan Road, Guangzhou 510641, ChinaDepartment of Transportation Engineering, South China University of Technology, 381 Wushan Road, Guangzhou 510641, ChinaDepartment of Transportation Engineering, South China University of Technology, 381 Wushan Road, Guangzhou 510641, ChinaGuangzhou Urban Planning & Design Survey Research Institute, 10 Jianshe Damalu, Guangzhou 510060, ChinaGuangzhou Urban Planning & Design Survey Research Institute, 10 Jianshe Damalu, Guangzhou 510060, ChinaThe urban road network is a large and complex system characterized by significant heterogeneity arising from different spatial structures and traffic demands. To facilitate effective management and control, it is necessary to partition the road network into homogeneous sub-areas. In this regard, we aim to propose a hybrid method for partitioning sub-areas with intra-area homogeneity, inter-area heterogeneity, and similar sizes, called CSDRA. It is specifically designed for bidirectional road networks with segment weights that encompass traffic flow, speed, or roadside facility evaluation. Based on community detection and spectral clustering, this proposed method comprises four main modules: initial partition, partitioning of large sub-areas, reassignment of small sub-areas, and boundary adjustment. In the preliminary partitioning work, we also design a road network reconstruction method which further helps to enhance the intra-area homogeneity and inter-area heterogeneity of partitioning results. Furthermore, to align with the requirement for comparable work units in practical traffic management and control, we control the similarity in the size of sub-areas by enforcing upper and lower bound constraints on the size of the sub-areas. We verify the outperformance of the proposed method by an experiment on the partitioning of an urban road network in Guangzhou, China, where we employ sidewalk barrier-free score data as segment weights. The results demonstrate the effectiveness of both the road network reconstruction method and the CSDRA proposed in this paper, as they significantly improve the partitioning outcomes compared with other methods using different evaluation indicators corresponding to the partitioning objectives. Finally, we investigate the influence of constraint parameters on the evaluation indicator. Our findings indicate that appropriately configuring these constraint parameters can effectively minimize sub-region size variations while having minimal impact on other aspects.https://www.mdpi.com/2220-9964/12/8/327bidirectional road network partitioninggraph reconstructionmulti-objectivescommunity detectionspectral clustering |
| spellingShingle | Yingying Ma Minglang Xu Xiaoran Qin Ying Zeng Lingyu Zeng Research on Road Network Partitioning Considering the Coupling of Network Connectivity and Traffic Attributes ISPRS International Journal of Geo-Information bidirectional road network partitioning graph reconstruction multi-objectives community detection spectral clustering |
| title | Research on Road Network Partitioning Considering the Coupling of Network Connectivity and Traffic Attributes |
| title_full | Research on Road Network Partitioning Considering the Coupling of Network Connectivity and Traffic Attributes |
| title_fullStr | Research on Road Network Partitioning Considering the Coupling of Network Connectivity and Traffic Attributes |
| title_full_unstemmed | Research on Road Network Partitioning Considering the Coupling of Network Connectivity and Traffic Attributes |
| title_short | Research on Road Network Partitioning Considering the Coupling of Network Connectivity and Traffic Attributes |
| title_sort | research on road network partitioning considering the coupling of network connectivity and traffic attributes |
| topic | bidirectional road network partitioning graph reconstruction multi-objectives community detection spectral clustering |
| url | https://www.mdpi.com/2220-9964/12/8/327 |
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