TY - JOUR PY - 2019// TI - A geographically weighted regression to estimate the comprehensive cost of traffic crashes at a zonal level JO - Accident analysis and prevention A1 - Hezaveh, Amin Mohamadi A1 - Arvin, Ramin A1 - Cherry, Christopher R. SP - 15 EP - 24 VL - 131 IS - N2 - 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.

Language: en

LA - en SN - 0001-4575 UR - http://dx.doi.org/10.1016/j.aap.2019.05.028 ID - ref1 ER -