Spatial and Temporal Distribution Analysis of Traffic Accidents Using GIS-Based Data in Harbin
Road traffic safety is a social issue of widespread concern. It is important for traffic managers to understand the distribution patterns of road traffic accidents. To this end, this study examines the spatial and temporal patterns of road traffic accidents from both accident frequency and accident...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2021/9207500 |
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| _version_ | 1849684454548701184 |
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| author | Meina Wang Jing Yi Xirui Chen Wenhui Zhang Tiangang Qiang |
| author_facet | Meina Wang Jing Yi Xirui Chen Wenhui Zhang Tiangang Qiang |
| author_sort | Meina Wang |
| collection | DOAJ |
| description | Road traffic safety is a social issue of widespread concern. It is important for traffic managers to understand the distribution patterns of road traffic accidents. To this end, this study examines the spatial and temporal patterns of road traffic accidents from both accident frequency and accident severity perspectives. Road traffic accident data from 2016 to 2018 in Harbin, China, were used for the analysis. First, the spatial localization of accidents was completed using geocoding, and the localized accident data were classified by season. Then, density analysis was performed both with and without considering road network density. The results of the density analysis showed that when road network density was considered, accidents were mainly distributed in urban centers, while accidents were more dispersed when road network density was not considered. Third, a cluster analysis considering accident severity found that low-severity accident clusters occurred mostly in urban centers. High-severity accident clusters were mostly present in suburban areas. Finally, the results of these two methods are shown by using the comap technique. Areas of the city with a high frequency and severity of crashes in each season were identified. This study will help traffic management to have a more visual and intuitive understanding of the urban traffic safety situation and to take targeted measures to improve it accordingly. |
| format | Article |
| id | doaj-art-c238276dd55b4841b784f6da80c2908d |
| institution | DOAJ |
| issn | 0197-6729 2042-3195 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-c238276dd55b4841b784f6da80c2908d2025-08-20T03:23:27ZengWileyJournal of Advanced Transportation0197-67292042-31952021-01-01202110.1155/2021/92075009207500Spatial and Temporal Distribution Analysis of Traffic Accidents Using GIS-Based Data in HarbinMeina Wang0Jing Yi1Xirui Chen2Wenhui Zhang3Tiangang Qiang4School of Traffic and Transportation, Northeast Forestry University, Harbin 150040, ChinaSchool of Traffic and Transportation, Northeast Forestry University, Harbin 150040, ChinaSchool of Traffic and Transportation, Northeast Forestry University, Harbin 150040, ChinaSchool of Traffic and Transportation, Northeast Forestry University, Harbin 150040, ChinaSchool of Traffic and Transportation, Northeast Forestry University, Harbin 150040, ChinaRoad traffic safety is a social issue of widespread concern. It is important for traffic managers to understand the distribution patterns of road traffic accidents. To this end, this study examines the spatial and temporal patterns of road traffic accidents from both accident frequency and accident severity perspectives. Road traffic accident data from 2016 to 2018 in Harbin, China, were used for the analysis. First, the spatial localization of accidents was completed using geocoding, and the localized accident data were classified by season. Then, density analysis was performed both with and without considering road network density. The results of the density analysis showed that when road network density was considered, accidents were mainly distributed in urban centers, while accidents were more dispersed when road network density was not considered. Third, a cluster analysis considering accident severity found that low-severity accident clusters occurred mostly in urban centers. High-severity accident clusters were mostly present in suburban areas. Finally, the results of these two methods are shown by using the comap technique. Areas of the city with a high frequency and severity of crashes in each season were identified. This study will help traffic management to have a more visual and intuitive understanding of the urban traffic safety situation and to take targeted measures to improve it accordingly.http://dx.doi.org/10.1155/2021/9207500 |
| spellingShingle | Meina Wang Jing Yi Xirui Chen Wenhui Zhang Tiangang Qiang Spatial and Temporal Distribution Analysis of Traffic Accidents Using GIS-Based Data in Harbin Journal of Advanced Transportation |
| title | Spatial and Temporal Distribution Analysis of Traffic Accidents Using GIS-Based Data in Harbin |
| title_full | Spatial and Temporal Distribution Analysis of Traffic Accidents Using GIS-Based Data in Harbin |
| title_fullStr | Spatial and Temporal Distribution Analysis of Traffic Accidents Using GIS-Based Data in Harbin |
| title_full_unstemmed | Spatial and Temporal Distribution Analysis of Traffic Accidents Using GIS-Based Data in Harbin |
| title_short | Spatial and Temporal Distribution Analysis of Traffic Accidents Using GIS-Based Data in Harbin |
| title_sort | spatial and temporal distribution analysis of traffic accidents using gis based data in harbin |
| url | http://dx.doi.org/10.1155/2021/9207500 |
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