The Impacts of Multiscale Urban Road Network Centrality on Taxi Travel: A Case Study in Shenzhen
As a crucial part of the urban system, road networks play a key role in the evolution of the urban structure. Therefore, studying the structural characteristics of urban road networks is pivotal for improving the efficiency of traffic network nodes and for relieving traffic pressure. This paper appl...
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2022/1780667 |
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| author | Dan Wang Yongxi Gong Xin Zhang Yaoyu Lin |
| author_facet | Dan Wang Yongxi Gong Xin Zhang Yaoyu Lin |
| author_sort | Dan Wang |
| collection | DOAJ |
| description | As a crucial part of the urban system, road networks play a key role in the evolution of the urban structure. Therefore, studying the structural characteristics of urban road networks is pivotal for improving the efficiency of traffic network nodes and for relieving traffic pressure. This paper applies an urban road network analysis method to measure the centrality of the multiscale road network in Shenzhen, China. Taxi GPS data from October 17 to October 23, 2017, were selected for analysis of spatial distribution characteristics. This paper also established a regression model of taxi pick-up and drop-off frequency and road network centrality for further analysis. Several interesting observations were made. With respect to the increasing search radius, the closeness centrality indicator shifts from a multicentered distribution to a single-centered distribution, while the betweenness centrality indicator shifts from a patchy distribution to a distribution along the main roads. In addition, the straightness centrality indicator turns from a dispersed distribution to a point-axis distribution, concentrated in the southern part of the city. Second, there were variations between the centrality of the road network and the location of taxi pick-up and drop-off points. The regression model gets the highest value of R2, indicating a significant correlation in cases where the search radius is 3 km. Finally, the relationship exhibits a clear positive correlation between the betweenness centrality and taxi pick-up and drop-off points. On the other hand, closeness centrality is not correlated with these points. The straightness centrality has a negative correlation with the frequency of taxi pick-up and drop-off at 3 km and 8 km scale. |
| format | Article |
| id | doaj-art-e66187dff04141689c6504327c2f5ac4 |
| institution | OA Journals |
| issn | 1099-0526 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-e66187dff04141689c6504327c2f5ac42025-08-20T02:21:03ZengWileyComplexity1099-05262022-01-01202210.1155/2022/1780667The Impacts of Multiscale Urban Road Network Centrality on Taxi Travel: A Case Study in ShenzhenDan Wang0Yongxi Gong1Xin Zhang2Yaoyu Lin3School of ArchitectureSchool of ArchitectureShenzhen Museng Architectural Design and Consultation Co LtdSchool of ArchitectureAs a crucial part of the urban system, road networks play a key role in the evolution of the urban structure. Therefore, studying the structural characteristics of urban road networks is pivotal for improving the efficiency of traffic network nodes and for relieving traffic pressure. This paper applies an urban road network analysis method to measure the centrality of the multiscale road network in Shenzhen, China. Taxi GPS data from October 17 to October 23, 2017, were selected for analysis of spatial distribution characteristics. This paper also established a regression model of taxi pick-up and drop-off frequency and road network centrality for further analysis. Several interesting observations were made. With respect to the increasing search radius, the closeness centrality indicator shifts from a multicentered distribution to a single-centered distribution, while the betweenness centrality indicator shifts from a patchy distribution to a distribution along the main roads. In addition, the straightness centrality indicator turns from a dispersed distribution to a point-axis distribution, concentrated in the southern part of the city. Second, there were variations between the centrality of the road network and the location of taxi pick-up and drop-off points. The regression model gets the highest value of R2, indicating a significant correlation in cases where the search radius is 3 km. Finally, the relationship exhibits a clear positive correlation between the betweenness centrality and taxi pick-up and drop-off points. On the other hand, closeness centrality is not correlated with these points. The straightness centrality has a negative correlation with the frequency of taxi pick-up and drop-off at 3 km and 8 km scale.http://dx.doi.org/10.1155/2022/1780667 |
| spellingShingle | Dan Wang Yongxi Gong Xin Zhang Yaoyu Lin The Impacts of Multiscale Urban Road Network Centrality on Taxi Travel: A Case Study in Shenzhen Complexity |
| title | The Impacts of Multiscale Urban Road Network Centrality on Taxi Travel: A Case Study in Shenzhen |
| title_full | The Impacts of Multiscale Urban Road Network Centrality on Taxi Travel: A Case Study in Shenzhen |
| title_fullStr | The Impacts of Multiscale Urban Road Network Centrality on Taxi Travel: A Case Study in Shenzhen |
| title_full_unstemmed | The Impacts of Multiscale Urban Road Network Centrality on Taxi Travel: A Case Study in Shenzhen |
| title_short | The Impacts of Multiscale Urban Road Network Centrality on Taxi Travel: A Case Study in Shenzhen |
| title_sort | impacts of multiscale urban road network centrality on taxi travel a case study in shenzhen |
| url | http://dx.doi.org/10.1155/2022/1780667 |
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