The Influence of Traffic, Land Use and Context Variables on Urban Crash Types (Case study: Shiraz Metropolis)

Built environmental factors are one of the most important causes of urban accidents. Studies have shown that in addition to accident data, which have spatial heterogeneity, factors influencing accidents also have spatial correlation. The occurrence of urban accidents depends on many human and environmental factors, so identifying the important factors influencing accidents and their spatial effects on each other is of great importance. The main goal of this study is to evaluate the spatial effects of environmental factors on the frequency of accidents in the city of Shiraz, Iran at the TAZ level. In the first step of the study, using component analysis models, important environmental factors affecting the accident were identified and composite indicators were produced as independent variables. In the second step, in order to control the effect of correlation and heterogeneity of model variables, spatial statistical models based on Euclidean distance such as geographically weighted Poisson regression (GWPR), geographically weighted negative binomial distribution (GWNBR) as well as Poisson and distribution models Negative binomial based on neighbor distance is used in spatial Bayes method with INLA approach. The results of the study showed that models based on distance and contiguity in order to evaluate the spatial effects of accident data and the factors affecting it at the TAZ level have higher accuracy than geographic weighted regression models, as well as indicators of land use diversity and access to the system. The public transport produced in the first step is effective in increasing the frequency of accidents, and in TAZs where this index is high, there is a higher probability of an accident. The results of this study can be important for city managers and planners in order to improve inner city safety measures as well as development planning and future city measures.

کلیدواژه ها:

land use ، Environmental Factors ، Urban Crash ، spatial effect based on neighbourhood ، Spatial effect based on Sistance Matrix