Literature DB >> 31233992

A geographically weighted regression to estimate the comprehensive cost of traffic crashes at a zonal level.

Amin Mohamadi Hezaveh1, Ramin Arvin1, Christopher R Cherry2.   

Abstract

Global road safety records demonstrate spatial variation of comprehensive cost of traffic crashes across countries. To the best of our knowledge, no study has explored the variation of this matter at a local geographical level. This study proposes a method to estimate the comprehensive crash cost at the zonal level by using person-injury cost. 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. 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. Using crash data from Tennessee, we assign those involved in traffic crashes to the census tract corresponding to their home address. The average Comprehensive Crash Cost at the Zonal Level (CCCAZ) for the period of the study was $18.2 million (2018 dollars). Poisson and Geographically Weighted Poisson Regression (GWPR) models were used to analyzing the data. The GWPR model was more suitable compared to the global model to address spatial heterogeneity. 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. 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 are discussed in line with road safety literature.
Copyright © 2019 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Comprehensive crash cost; Geographically weighted regression; Home-based approach; Road safety

Mesh:

Year:  2019        PMID: 31233992     DOI: 10.1016/j.aap.2019.05.028

Source DB:  PubMed          Journal:  Accid Anal Prev        ISSN: 0001-4575


  2 in total

1.  A Spatial Autoregressive Quantile Regression to Examine Quantile Effects of Regional Factors on Crash Rates.

Authors:  Tianjian Yu; Fan Gao; Xinyuan Liu; Jinjun Tang
Journal:  Sensors (Basel)       Date:  2021-12-21       Impact factor: 3.576

2.  Determinants and Prediction of Injury Severities in Multi-Vehicle-Involved Crashes.

Authors:  Xiuguang Song; Rendong Pi; Yu Zhang; Jianqing Wu; Yuhuan Dong; Han Zhang; Xinyuan Zhu
Journal:  Int J Environ Res Public Health       Date:  2021-05-15       Impact factor: 3.390

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.