The Spatiotemporal Traffic Accident Risk Analysis in Urban Traffic Network

Traffic accidents seriously threaten people’s lives and property all over the world. Therefore, it is of great significance to human society to have a long-term traffic accidents data with detail temporal and geographic information in a specific space, which can be used for traffic accident hotspots identification to reduce the incidence of traffic accidents. Here, we obtain a one-year dataset of traffic accidents of the city center in Changchun, Northeast China, in 2017. In this paper, we analyze the risk of traffic accident in urban area, and then discover the characteristics of traffic accidents at the temporal and spatial aspect. We construct a traffic network, which takes crossings as nodes and road sections as edges and weighted by the total number of traffic accidents. In addition, we integrate road structure data and meteorological data to explore the characteristics of the traffic network.