mohammad bavar

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.

The type of land use in each traffic area zone (TAZ) is the most important factor determining the number of vehicles, geometric and traffic characteristics in that zone. Any factor in the urban environment that causes congestion and attraction of vehicles at certain times increases the probability of a crash in that area. The purpose of this study is to investigate the effect of the share of different types of uses in various traffic areas of Shiraz city on the probability of a crash. A two-step method, including identifying the types of uses influencing the occurrence of crashes and spatial effects between independent variables and crash data in space Kernel density estimate (KDE) methods, has also been used to find the suitable bandwidth for searching observations. In order to investigate the spatial effects of land use types on crash incidence, geographically weighted regressions (GWRs) and geographically weighted Poisson regressions (GWPRs) were used. Based on the validation criteria, the local GWPR model performs better than the global Poisson model and the local GWR model among the mentioned models .Additionally, the presence of residential, commercial, barren, and abandoned uses, as well as the mixing of residential and non-residential uses, significantly impact crashes. Examining the spatial effects of land use types in this study's traffic areas can be very important in carrying out safety measures.