چكيده به لاتين
In the field of urban traffic safety, a fundamental challenge for decision-makers is making long-term decisions to reduce accidents. One of them is deciding on how to arrange the city and the placement of its components. In this context, the city's transportation network, consisting of intersections and road segments, can be conceived as a graph composed of nodes and edges. The relationships between the components of the graph (urban network) and its structural features can play a significant role in predicting and reducing intra-city accidents. In this study, an attempt has been made to improve the understanding of the structural relationships within the city network and their impact on traffic safety by calculating structural indices such as closeness centrality, betweenness centrality, eigenvector centrality, eccentricity, and page rank for the edges of the city graph. These indices, along with other relevant variables, are used as predictor variables in multilevel hierarchical models to comprehend the structural relationships of the city network and their influence on traffic safety. The study was conducted in Mashhad, covering an area with 50 traffic zones, and multilevel hierarchical models were employed to recognize the hierarchical structure of accident data and the heterogeneity among different traffic zones, considering the various effects of variables in predicting accident frequency on 16,610 edges of the road network in this area. The results of this research indicate that the structural features of the city network, especially betweenness centrality and page rank, directly and inversely impact the frequency of urban accidents. According to the findings of this study, one of the suggestions could be for urban planners and designers to focus less on vehicular mobility and include patterns that consist of central areas with high levels of closeness centrality and eigenvector centrality. These designs, by reducing speed and facilitating secure access to the edges of other city sections, can contribute to the overall safety of the city. The results of this study not only contribute to improving the transportation system and increasing traffic safety but also provide useful information to city managers for making optimal decisions.
