Development and application of traffic accident density estimation models using kernel density estimation

Hashimoto, Seiji; Yoshiki, Syuji; Saeki, Ryoko; Mimura, Yasuhiro; Ando, Ryosuke; Nanba, Shutaro

doi:10.1016/j.jtte.2016.01.005

Cited by 63 publications

(28 citation statements)

References 20 publications

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“…The most straightforward use of GIS for crash analysis is the examination of spatial characteristics of crash locations [11]. Several studies have analyzed the traffic crash characteristics from spatial perspectives, and primarily by analyzing the road network density through kernel density estimation in 2D space [12][13][14][15]. In addition, numerous studies have also used spatial autocorrelation functions based on GIS to identify the traffic crash hotspot [16][17][18][19][20].…”

Section: Two-dimensional Spatial Analysismentioning

confidence: 99%

Traffic Crash Evolution Characteristic Analysis and Spatiotemporal Hotspot Identification of Urban Road Intersections

Cheng

Lü

2018

Sustainability

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Road traffic safety is a key concern of transport management as it has severely restricted Chinese economic and social development. With the objective to prevent and reduce road traffic crashes, this study proposes a comprehensive spatiotemporal analysis method that integrates the time-space cube analysis, spatial autocorrelation analysis, and emerging hot spot analysis for exploring the traffic crash evolution characteristics and identifying crash hot spots. These analyses are all conducted by the corresponding toolbox of ArcGIS 10.5. Then, a small sized-city of China (i.e., Wujiang) is selected as the case study, and the historical traffic crash data occurring at the road intersections of Wujiang for the year 2016 are analyzed by the proposed method. The analysis process identifies the high incidence locations of traffic crashes, then presents the spatial change trend and statistical significance of the crash locations. Finally, different types of crash hotspots, as well as their evolution patterns over time, are determined. The results illustrate that the traffic crash hotspots of road intersections are primarily distributed in the Northeast area of Wujiang’s major urban area, while the crash cold spots are concentrated in the Southwest of Wujiang, which points out the direction for crash prevention. In addition, the finding has a potential engineering application value, and it is of great significance to the sustainable development of Wujiang.

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Section: Two-dimensional Spatial Analysismentioning

confidence: 99%

Traffic Crash Evolution Characteristic Analysis and Spatiotemporal Hotspot Identification of Urban Road Intersections

Cheng

Lü

2018

Sustainability

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“…Since those values of the difference were normally distributed, a simple z score was used to test significance (PCS mean −0.031, SD 2.47, non-PCS −0.688, SD 3.06) 37. Again, the definition of a ‘hot spot’ relies mostly on subjective decisions related to threshold 28. Accordingly, only raster values of +/-3 SD significant at the 5% level were mapped to identify major changes in spatial patterns.…”

Section: Methodsmentioning

confidence: 99%

Spatial distribution of pedestrian-motor vehicle collisions before and after pedestrian countdown signal installation in Toronto, Canada

et al. 2017

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“…GIS can be applied to a wide range of fields, such as the environmental disasters, sustainable energy, endemic control, agriculture, health, urban planning, demographic survey, and traffic (CHINGOMBE et al, 2015;CRISTEA, JOCEA, 2015;YASOBANT et al, 2015;ABDELRAHMAN, NATARAJAN, HEGDE, 2016;GUPTA et al, 2016;HASHIMOTO et al, 2016;JEMAL, AL-THUKAIR, 2016;NORTH, MILLER, 2017). Regarding traffic, the most important are research on accidents and route optimization (IVAN et al, 2015;ELSHEIKH et al, 2016).…”

Section: Sistema De Información Geográfica En Análisis Espacial De Acmentioning

confidence: 99%

Geographic Information System in the Spatial Analysis of Urban Traffic Accidents in Cascavel, Paraná, Brazil

Canton

Maltauro

Verica

et al. 2020

BARU

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considering the high rates of traffic accidents, care provided to victims must be fast and efficient. The objective was to analyze the density of traffic accidents and the profile of the victims assisted by the 4th Fire Department in Cascavel. It was also intended to analyze traffic signs and a place to build a new Fire Station. Geographic Information System and geoprocessing resources were used to identify the traffic accidents hotspots applying kernel density estimation. The victims' profile and their association with the severity of the injuries were obtained based on the chi-square statistic and the correspondence analysis. Field data were investigated to verify traffic signs at accident locations that involved victims with severity of more serious injuries. Most accidents occurred in the afternoon, involving men between 18 and 30 years old. Running over was the occurrence that most stood out considering the severity of the victims, with locations without any traffic signs. Moreover, a plot that meets all the requested criteria and is located in a region of high occurences of traffic accidents was found to build the new station.

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Development and application of traffic accident density estimation models using kernel density estimation

Cited by 63 publications

References 20 publications

Traffic Crash Evolution Characteristic Analysis and Spatiotemporal Hotspot Identification of Urban Road Intersections

Traffic Crash Evolution Characteristic Analysis and Spatiotemporal Hotspot Identification of Urban Road Intersections

Spatial distribution of pedestrian-motor vehicle collisions before and after pedestrian countdown signal installation in Toronto, Canada

Geographic Information System in the Spatial Analysis of Urban Traffic Accidents in Cascavel, Paraná, Brazil

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