![]() Spatial autocorrelation and skewed distribution are the most frequent issues in crash rate modelling analysis. This study has shown the dispersion and density of pedestrian crashes without having the volume of pedestrians and thus can be done by taking safety measures in places prone to pedestrian crashes. The weighted negative binomial distribution could moderate the amount of heterogeneity of crash data to some extent. The Moran and Variance Inflated Factor (VIF) indices were also within acceptable limits. ![]() These models had the lowest values of Akaike Information Criterion (AIC), the lowest values of Cross Validation and the lowest values of Root Mean Square Error (RMSE). The results showed that GWZIPR and GWZINBR models make more accurate predictions. Finally, the EB model was extended to the Geographic Empirical Bayesian (Ge-EB) model. In this study, the areas analyzed for the development of the EB model based on pedestrian exposure variables include traffic analysis zones (TAZs). For doing so, four models of geographic weighted Poisson regression (GWPR), geographic weighted zero-inflated Poisson regression (GWZIPR), geographic weighted Negative Binomial regression (GWNBR) and the geographic weighted zero-inflated Negative Binomial regression (GWZINBR) have been used. The objective of this study is to estimate the expected geographical frequency of pedestrian crashes using the Empirical Bayesian (EB) approach using weighted geographical regression models for pedestrian crashes in Tehran. In this study, an EB model has been developed to estimate the expected frequency of pedestrian crashes in urban areas using the over-dispersion parameter taking into account the spatial correlation of crash data. Due to the lack of spatial correlation and instability in the crash data, the statistical reliability of Empirical Bayesian method in the combination of the observed and predicted crash frequency is questionable. Predicting pedestrian crashes on urban roads is one of the most important issues related to urban traffic safety. According to the HSM, the average expected crash frequency is estimated by the combination of observed and predicted crash frequencies using the Negative Binomial model, assuming that the time and place of the relationship between crash frequency and the affecting factors is constant. However, by increasing the availability of crash geographic data, new methods of spatial analysis, geographic weighted regression, and increasing computational power, the hypothesis of stagnation in crash data can be adjusted (Li et al., 2013 Da Silva and Rodrigues, 2014 Xu and Huang, 2015 Dai and Jaworski, 2016 Gomes et al., 2017 Liu et al., 2017 Huang et al., 2018 Hezaveh et al., 2019 Champahom et al., 2020 Gu et al., 2020 Obelheiro et al., 2020 Oluwajana et al., 2020 Soroori et al., 2020 and Zeng et al., 2020). Lord et al., 2007 Aguero-Valverde, 2013 Sharma and Landge, 2013 Dong et al., 2014 Klein et al., 2015 Dai and Jaworski, 2016 Hezaveh et al., 2019 Yu et al., 2019 Gu et al., 2020 and Obelheiro et al., 2020). Findings are discussed in line with road safety literature. Alternatively, VMT, vehicle per capita, percent educated over 25-year-old, population under 16-year-old, and proportion of non-white races and individuals who use a motorcycle as their commute mode have a positive association with CCCAZ. Findings indicate population of people over 60-years-old, the proportion of residents that use non-motorized transportation, household income, population density, household size, and metropolitan indicator have a negative association with CCCAZ. The GWPR model was more suitable compared to the global model to address spatial heterogeneity. Poisson and Geographically Weighted Poisson Regression (GWPR) models were used to analyzing the data. The average Comprehensive Crash Cost at the Zonal Level (CCCAZ) for the period of the study was $18.2 million (2018 dollars). Using crash data from Tennessee, we assign those involved in traffic crashes to the census tract corresponding to their home address. To overcome this limitation, we defined Home-Based Approach crash frequency as the expected number of crashes by severity that road users who live in a certain geographic area have during a specified period. The current metric of road safety attributes safety to the location of the crash, which makes it challenging to assign the crash cost to home-location of the individuals who were involved in traffic crashes. ![]() This study proposes a method to estimate the comprehensive crash cost at the zonal level by using person-injury cost. To the best of our knowledge, no study has explored the variation of this matter at a local geographical level. Global road safety records demonstrate spatial variation of comprehensive cost of traffic crashes across countries.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |