|
This paper used SPSS statistical analysis and GIS spatial analysis to construct an analytical framework based on urban traffic crime data. The case location record of dangerous driving offences, traffic accident crimes and offences against public safety from 2016-2020 on the China Judgements Online was used as the data foundation. Taking an empirical study further interpreted the distribution characteristics and influencing factors of the traffic crime phenomenon in the central city of Wuhan. The findings were as follows in the central city of Wuhan from 2016 to 2020. (1) The number of traffic crimes showed relatively obvious characteristics in terms of temporal differences. The fluctuations of the yearly, monthly and hourly data were the most obvious, while the fluctuations of the daily data were more random. (2) The overall spatial distribution of traffic crime points showed a dispersion process to agglomeration yearly by using average nearest neighbour analysis, but the degree of aggregation was not high. Spatial autocorrelation analysis showed that the positive spatial correlation of crime points was relatively apparent, but the difference in clustering local crime points was slight. (3) The kernel density estimation results indicated that traffic crime generally showed an elliptical trend in the northeast-southwest direction. The distribution centre of traffic crime points shifted from Wuhan Wuchang to Wuhan Hankou and Wuhan Hanyang. In addition, crime hotspots and repeat crime hotspots indicated a situation of high hotspots in the Yangchunhu area of Wuhan Qingshan and sub-high hotspots in the Wangjiawan area of Wuhan Hanyang. It was influenced by factors from the industrial region's layout, crowding and traffic safety on the river bridge. (4) The causes of traffic crime included the gender of traffic crime subjects, the type of vehicle and the origin of the vehicle's place. The gender of drivers, the number of private cars, and the type of accident-prone vehicles had an impact on traffic crime. Moreover, the crime hotspots showed a more obvious consistency with the degree of traffic road integration, but the correlation with traffic road complexity was relatively insignificant.
|
