Severity, Spatial Pattern and Statistical Analysis of Road Traffic Crash Hot Spots in Ethiopia
The reduction of traffic crashes, as well as their socio-economic consequences, has captivated the attention of safety professionals and transportation agencies. The most important activity for an effective road safety practice is to identify hazardous roadway areas based on a spatial pattern analys...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-09-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/11/19/8828 |
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| author | Alamirew Mulugeta Tola Tamene Adugna Demissie Fokke Saathoff Alemayehu Gebissa |
| author_facet | Alamirew Mulugeta Tola Tamene Adugna Demissie Fokke Saathoff Alemayehu Gebissa |
| author_sort | Alamirew Mulugeta Tola |
| collection | DOAJ |
| description | The reduction of traffic crashes, as well as their socio-economic consequences, has captivated the attention of safety professionals and transportation agencies. The most important activity for an effective road safety practice is to identify hazardous roadway areas based on a spatial pattern analysis of crashes and an evaluation of crash spatial relations with neighboring areas and other relevant factors. For decades, safety researchers have adopted several techniques to analyze historical road traffic crash (RTC) information using the advanced GIS-based hot spot analysis. The objective of this study is to present a GIS technique for identifying crash hot spots based on spatial autocorrelation analysis using a four-year (2014–2017) crash data across Ethiopian regions, as well as zones and towns in the Oromia region. The study considered the corresponding severity values of RTCs for the analysis and ranking of crash hot spot areas. The spatial autocorrelation tool in ArcGIS 10.5 was used to analyze the spatial patterns of RTCs and then the Getis Ord <i>Gi*</i> statistics tool was used to identify high and low crash severity cluster zones. The results showed that the methods used in this analysis, which incorporated Moran’s I spatial autocorrelation of crash incidents, Getis Ord <i>Gi*</i> and crash severity index, proved to be a fruitful strategy for identifying and ranking crash hot spots. The identified crash hot spot areas are along the entrance to and exit from Addis Ababa, Ethiopia’s capital city, so the responsible bodies and traffic management agencies should give top priority attention and conduct a thorough study to reduce the socio-economic effect of RTCs. |
| first_indexed | 2024-03-10T07:07:04Z |
| format | Article |
| id | doaj.art-ca7d6cbf32384202b8c752a0327bf7c7 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T07:07:04Z |
| publishDate | 2021-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-ca7d6cbf32384202b8c752a0327bf7c72023-11-22T15:43:35ZengMDPI AGApplied Sciences2076-34172021-09-011119882810.3390/app11198828Severity, Spatial Pattern and Statistical Analysis of Road Traffic Crash Hot Spots in EthiopiaAlamirew Mulugeta Tola0Tamene Adugna Demissie1Fokke Saathoff2Alemayehu Gebissa3Faculty of Agricultural and Environmental Sciences, Geotechnics and Coastal Engineering, Rostock University, 18051 Rostock, GermanyFaculty of Civil & Environmental Engineering, Jimma University, Jimma 378, EthiopiaFaculty of Agricultural and Environmental Sciences, Geotechnics and Coastal Engineering, Rostock University, 18051 Rostock, GermanyFaculty of Agricultural and Environmental Sciences, Geotechnics and Coastal Engineering, Rostock University, 18051 Rostock, GermanyThe reduction of traffic crashes, as well as their socio-economic consequences, has captivated the attention of safety professionals and transportation agencies. The most important activity for an effective road safety practice is to identify hazardous roadway areas based on a spatial pattern analysis of crashes and an evaluation of crash spatial relations with neighboring areas and other relevant factors. For decades, safety researchers have adopted several techniques to analyze historical road traffic crash (RTC) information using the advanced GIS-based hot spot analysis. The objective of this study is to present a GIS technique for identifying crash hot spots based on spatial autocorrelation analysis using a four-year (2014–2017) crash data across Ethiopian regions, as well as zones and towns in the Oromia region. The study considered the corresponding severity values of RTCs for the analysis and ranking of crash hot spot areas. The spatial autocorrelation tool in ArcGIS 10.5 was used to analyze the spatial patterns of RTCs and then the Getis Ord <i>Gi*</i> statistics tool was used to identify high and low crash severity cluster zones. The results showed that the methods used in this analysis, which incorporated Moran’s I spatial autocorrelation of crash incidents, Getis Ord <i>Gi*</i> and crash severity index, proved to be a fruitful strategy for identifying and ranking crash hot spots. The identified crash hot spot areas are along the entrance to and exit from Addis Ababa, Ethiopia’s capital city, so the responsible bodies and traffic management agencies should give top priority attention and conduct a thorough study to reduce the socio-economic effect of RTCs.https://www.mdpi.com/2076-3417/11/19/8828crash severityGetis Ord <i>Gi*</i>road traffic crash (RTC)spatial autocorrelation |
| spellingShingle | Alamirew Mulugeta Tola Tamene Adugna Demissie Fokke Saathoff Alemayehu Gebissa Severity, Spatial Pattern and Statistical Analysis of Road Traffic Crash Hot Spots in Ethiopia Applied Sciences crash severity Getis Ord <i>Gi*</i> road traffic crash (RTC) spatial autocorrelation |
| title | Severity, Spatial Pattern and Statistical Analysis of Road Traffic Crash Hot Spots in Ethiopia |
| title_full | Severity, Spatial Pattern and Statistical Analysis of Road Traffic Crash Hot Spots in Ethiopia |
| title_fullStr | Severity, Spatial Pattern and Statistical Analysis of Road Traffic Crash Hot Spots in Ethiopia |
| title_full_unstemmed | Severity, Spatial Pattern and Statistical Analysis of Road Traffic Crash Hot Spots in Ethiopia |
| title_short | Severity, Spatial Pattern and Statistical Analysis of Road Traffic Crash Hot Spots in Ethiopia |
| title_sort | severity spatial pattern and statistical analysis of road traffic crash hot spots in ethiopia |
| topic | crash severity Getis Ord <i>Gi*</i> road traffic crash (RTC) spatial autocorrelation |
| url | https://www.mdpi.com/2076-3417/11/19/8828 |
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