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 prop...
We have proposed a data-driven method for spatio-temporal analysis of car crashes based on the Multi...
AbstractThe consideration of spatial externalities in traffic safety analysis is of paramount import...
Exploring spatiotemporal patterns of traffic accidents from historic crash databases is one essentia...
The interaction among social economy, geography, and environment leads to the occurrence of traffic ...
The problem of road traffic safety has been widely concerned in recent years. The identification of ...
[EMBARGOED UNTIL 6/1/2023] One reality of transportation systems is that vehicular accidents can hap...
The occurrence of fatal traffic accidents often causes serious casualties and property losses, endan...
Research on spatial cluster detection of traffic crash (TC) at the city level plays an essential rol...
Big data analytics for traffic accidents is a hot topic and has significant values for a smart and s...
Rear-end collisions are caused by drivers misjudging urgent risks while following vehicles ahead in ...
Road traffic accidents (RTAs) rank in the top ten causes of the global burden of disease and injury,...
With the expansion and advancement of road infrastructures, many large cities are experiencing incre...
Road traffic collisions are recognized as a serious public health issue worldwide, with the identifi...
[[abstract]]Traffic accidents are frequently caused by complicated connection among people, vehicles...
Road traffic accidents (RTAs) rank in the top ten causes of the global burden of disease and injury,...
We have proposed a data-driven method for spatio-temporal analysis of car crashes based on the Multi...
AbstractThe consideration of spatial externalities in traffic safety analysis is of paramount import...
Exploring spatiotemporal patterns of traffic accidents from historic crash databases is one essentia...
The interaction among social economy, geography, and environment leads to the occurrence of traffic ...
The problem of road traffic safety has been widely concerned in recent years. The identification of ...
[EMBARGOED UNTIL 6/1/2023] One reality of transportation systems is that vehicular accidents can hap...
The occurrence of fatal traffic accidents often causes serious casualties and property losses, endan...
Research on spatial cluster detection of traffic crash (TC) at the city level plays an essential rol...
Big data analytics for traffic accidents is a hot topic and has significant values for a smart and s...
Rear-end collisions are caused by drivers misjudging urgent risks while following vehicles ahead in ...
Road traffic accidents (RTAs) rank in the top ten causes of the global burden of disease and injury,...
With the expansion and advancement of road infrastructures, many large cities are experiencing incre...
Road traffic collisions are recognized as a serious public health issue worldwide, with the identifi...
[[abstract]]Traffic accidents are frequently caused by complicated connection among people, vehicles...
Road traffic accidents (RTAs) rank in the top ten causes of the global burden of disease and injury,...
We have proposed a data-driven method for spatio-temporal analysis of car crashes based on the Multi...
AbstractThe consideration of spatial externalities in traffic safety analysis is of paramount import...
Exploring spatiotemporal patterns of traffic accidents from historic crash databases is one essentia...