Identifying Strong Connectivity in Urban Road Networks Considering Traffic Constraints: An Analysis of Road Networks With Different Patterns
Road network connectivity is an important indicator for measuring the operational efficiency and reliability of urban road networks, and it plays an important role in supporting traffic planning and management decisions. The implementation of traffic management measures, such as traffic bans and tem...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2025-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/atr/3589423 |
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| author | Ruru Xing ZePeng Yang Xinghua Zhang Yiwen Liang Tao Yang Fei Wang |
| author_facet | Ruru Xing ZePeng Yang Xinghua Zhang Yiwen Liang Tao Yang Fei Wang |
| author_sort | Ruru Xing |
| collection | DOAJ |
| description | Road network connectivity is an important indicator for measuring the operational efficiency and reliability of urban road networks, and it plays an important role in supporting traffic planning and management decisions. The implementation of traffic management measures, such as traffic bans and temporary traffic flow changes, will restrict access to some sections and lanes, reduce the passable paths in the road network, and thus affect the overall connectivity performance of the road network. Existing road network research results mostly evaluate the topological connectivity of the network at the physical level, and it is difficult to accurately portray the actual road network connectivity under traffic management conditions. To quantitatively evaluate the road network connectivity performance after the implementation of traffic management tools, this paper proposes a road network connectivity evaluation method based on strongly connected effective paths. Firstly, the node steering coefficients are used to describe the no-traffic constraints of turning lanes, and the connectivity evaluation indexes are constructed based on the number of strongly connected effective paths and the shortest paths of strongly connected paths. Secondly, combining the Floyd-Warshall algorithm and the depth-first search algorithm, we constructed a strong connectivity effective path search algorithm to adapt to the refined traffic management situation, and identified the key road sections that have the greatest impact on the connectivity of the road network by considering the maximum acceptable level of the path and the road access constraints. Finally, Sioux-Falls network and nine urban road networks with different layout patterns are selected for the case study and compared with traditional road network connectivity indicators. The case studies show that: (1) the connectivity of the square grid road network structure is superior, while the connectivity of the free-form road network is the lowest; (2) road access management measures reduce the overall road network connectivity, and the banning of traffic in critical sections has the most significant effect on connectivity. Accurately assessing the changes in road network connectivity performance under different traffic management measures provides a scientific basis for the development of road control strategies, which can effectively improve urban traffic fluency and residents’ travel efficiency. |
| format | Article |
| id | doaj-art-1f30fb1cae004d2b8ca215c85cd0a172 |
| institution | Kabale University |
| issn | 2042-3195 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-1f30fb1cae004d2b8ca215c85cd0a1722025-08-21T00:00:01ZengWileyJournal of Advanced Transportation2042-31952025-01-01202510.1155/atr/3589423Identifying Strong Connectivity in Urban Road Networks Considering Traffic Constraints: An Analysis of Road Networks With Different PatternsRuru Xing0ZePeng Yang1Xinghua Zhang2Yiwen Liang3Tao Yang4Fei Wang5Chongqing Key Laboratory of Intelligent Integrated and Multidimensional Transportation SystemOperations DepartmentChongqing Key Laboratory of Intelligent Integrated and Multidimensional Transportation SystemChongqing Key Laboratory of Intelligent Integrated and Multidimensional Transportation SystemSoftware Development DepartmentChongqing Key Laboratory of Intelligent Integrated and Multidimensional Transportation SystemRoad network connectivity is an important indicator for measuring the operational efficiency and reliability of urban road networks, and it plays an important role in supporting traffic planning and management decisions. The implementation of traffic management measures, such as traffic bans and temporary traffic flow changes, will restrict access to some sections and lanes, reduce the passable paths in the road network, and thus affect the overall connectivity performance of the road network. Existing road network research results mostly evaluate the topological connectivity of the network at the physical level, and it is difficult to accurately portray the actual road network connectivity under traffic management conditions. To quantitatively evaluate the road network connectivity performance after the implementation of traffic management tools, this paper proposes a road network connectivity evaluation method based on strongly connected effective paths. Firstly, the node steering coefficients are used to describe the no-traffic constraints of turning lanes, and the connectivity evaluation indexes are constructed based on the number of strongly connected effective paths and the shortest paths of strongly connected paths. Secondly, combining the Floyd-Warshall algorithm and the depth-first search algorithm, we constructed a strong connectivity effective path search algorithm to adapt to the refined traffic management situation, and identified the key road sections that have the greatest impact on the connectivity of the road network by considering the maximum acceptable level of the path and the road access constraints. Finally, Sioux-Falls network and nine urban road networks with different layout patterns are selected for the case study and compared with traditional road network connectivity indicators. The case studies show that: (1) the connectivity of the square grid road network structure is superior, while the connectivity of the free-form road network is the lowest; (2) road access management measures reduce the overall road network connectivity, and the banning of traffic in critical sections has the most significant effect on connectivity. Accurately assessing the changes in road network connectivity performance under different traffic management measures provides a scientific basis for the development of road control strategies, which can effectively improve urban traffic fluency and residents’ travel efficiency.http://dx.doi.org/10.1155/atr/3589423 |
| spellingShingle | Ruru Xing ZePeng Yang Xinghua Zhang Yiwen Liang Tao Yang Fei Wang Identifying Strong Connectivity in Urban Road Networks Considering Traffic Constraints: An Analysis of Road Networks With Different Patterns Journal of Advanced Transportation |
| title | Identifying Strong Connectivity in Urban Road Networks Considering Traffic Constraints: An Analysis of Road Networks With Different Patterns |
| title_full | Identifying Strong Connectivity in Urban Road Networks Considering Traffic Constraints: An Analysis of Road Networks With Different Patterns |
| title_fullStr | Identifying Strong Connectivity in Urban Road Networks Considering Traffic Constraints: An Analysis of Road Networks With Different Patterns |
| title_full_unstemmed | Identifying Strong Connectivity in Urban Road Networks Considering Traffic Constraints: An Analysis of Road Networks With Different Patterns |
| title_short | Identifying Strong Connectivity in Urban Road Networks Considering Traffic Constraints: An Analysis of Road Networks With Different Patterns |
| title_sort | identifying strong connectivity in urban road networks considering traffic constraints an analysis of road networks with different patterns |
| url | http://dx.doi.org/10.1155/atr/3589423 |
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