Quantitative Estimation and Analysis of Spatiotemporal Delay Effects in Expressway Traffic Accidents
Expressway traffic accidents often result in severe congestion, with their unpredictable nature complicating timely and effective response measures. This paper presents a comprehensive method for accurately estimating and analyzing the spatiotemporal delay effects of expressway accidents through the...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-11-01
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| Series: | ISPRS International Journal of Geo-Information |
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| Online Access: | https://www.mdpi.com/2220-9964/13/11/407 |
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| author | Yunfei Zhang Zhengrui Pan Fangqi Zhu Chaoyang Shi Xue Yang |
| author_facet | Yunfei Zhang Zhengrui Pan Fangqi Zhu Chaoyang Shi Xue Yang |
| author_sort | Yunfei Zhang |
| collection | DOAJ |
| description | Expressway traffic accidents often result in severe congestion, with their unpredictable nature complicating timely and effective response measures. This paper presents a comprehensive method for accurately estimating and analyzing the spatiotemporal delay effects of expressway accidents through the integration of multi-source geographic data. The innovation lies in utilizing real-world vehicle trajectory data, combined with a Traffic Performance Index (TPI), to quantitatively assess delay impacts. By applying spatial clustering and hotspot detection techniques, we investigate the distribution patterns of delays and further employ a Spatial Error Model (SEM) to examine the relationships between accident characteristics and associated delay effects. Using expressway accident data and vehicle trajectory records from Hunan Province, the results demonstrate that the TPI-based approach effectively captures the duration, extent, and severity of traffic delays. Moreover, significant correlations are identified between delay impacts and specific accident characteristics, such as accident type, road type, road environment, pre-accident vehicle speed, and secondary accidents. This approach provides traffic management authorities with actionable insights into the overall roadway impact, facilitating targeted emergency response strategies and informing road usage policies tailored to the characteristics of accident impacts, thus helping to mitigate future risks. |
| format | Article |
| id | doaj-art-bbe92286abeb43b6b1b78e0a5e296dcd |
| institution | Kabale University |
| issn | 2220-9964 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | ISPRS International Journal of Geo-Information |
| spelling | doaj-art-bbe92286abeb43b6b1b78e0a5e296dcd2024-11-26T18:06:27ZengMDPI AGISPRS International Journal of Geo-Information2220-99642024-11-01131140710.3390/ijgi13110407Quantitative Estimation and Analysis of Spatiotemporal Delay Effects in Expressway Traffic AccidentsYunfei Zhang0Zhengrui Pan1Fangqi Zhu2Chaoyang Shi3Xue Yang4School of Traffic and Transportation Engineering, Changsha University of Science and Technology, Changsha 410011, ChinaSchool of Traffic and Transportation Engineering, Changsha University of Science and Technology, Changsha 410011, ChinaSchool of Traffic and Transportation Engineering, Changsha University of Science and Technology, Changsha 410011, ChinaSchool of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan 430079, ChinaSchool of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, ChinaExpressway traffic accidents often result in severe congestion, with their unpredictable nature complicating timely and effective response measures. This paper presents a comprehensive method for accurately estimating and analyzing the spatiotemporal delay effects of expressway accidents through the integration of multi-source geographic data. The innovation lies in utilizing real-world vehicle trajectory data, combined with a Traffic Performance Index (TPI), to quantitatively assess delay impacts. By applying spatial clustering and hotspot detection techniques, we investigate the distribution patterns of delays and further employ a Spatial Error Model (SEM) to examine the relationships between accident characteristics and associated delay effects. Using expressway accident data and vehicle trajectory records from Hunan Province, the results demonstrate that the TPI-based approach effectively captures the duration, extent, and severity of traffic delays. Moreover, significant correlations are identified between delay impacts and specific accident characteristics, such as accident type, road type, road environment, pre-accident vehicle speed, and secondary accidents. This approach provides traffic management authorities with actionable insights into the overall roadway impact, facilitating targeted emergency response strategies and informing road usage policies tailored to the characteristics of accident impacts, thus helping to mitigate future risks.https://www.mdpi.com/2220-9964/13/11/407traffic accidentspatiotemporal delay effectquantitative analysisSEMexpressway |
| spellingShingle | Yunfei Zhang Zhengrui Pan Fangqi Zhu Chaoyang Shi Xue Yang Quantitative Estimation and Analysis of Spatiotemporal Delay Effects in Expressway Traffic Accidents ISPRS International Journal of Geo-Information traffic accident spatiotemporal delay effect quantitative analysis SEM expressway |
| title | Quantitative Estimation and Analysis of Spatiotemporal Delay Effects in Expressway Traffic Accidents |
| title_full | Quantitative Estimation and Analysis of Spatiotemporal Delay Effects in Expressway Traffic Accidents |
| title_fullStr | Quantitative Estimation and Analysis of Spatiotemporal Delay Effects in Expressway Traffic Accidents |
| title_full_unstemmed | Quantitative Estimation and Analysis of Spatiotemporal Delay Effects in Expressway Traffic Accidents |
| title_short | Quantitative Estimation and Analysis of Spatiotemporal Delay Effects in Expressway Traffic Accidents |
| title_sort | quantitative estimation and analysis of spatiotemporal delay effects in expressway traffic accidents |
| topic | traffic accident spatiotemporal delay effect quantitative analysis SEM expressway |
| url | https://www.mdpi.com/2220-9964/13/11/407 |
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