Association between Crash Attributes and Drivers' Crash Involvement: A Study Based on Police-Reported Crash Data.

Guofa Li,Weijian Lai,Xingda Qu

doi:10.3390/ijerph17239020

Abstract

Understanding the association between crash attributes and drivers’ crash involvement in different types of crashes can help figure out the causation of crashes. The aim of this study was to examine the involvement in different types of crashes for drivers from different age groups, by using the police-reported crash data from 2014 to 2016 in Shenzhen, China. A synthetic minority oversampling technique (SMOTE) together with edited nearest neighbors (ENN) were used to solve the data imbalance problem caused by the lack of crash records of older drivers. Logistic regression was utilized to estimate the probability of a certain type of crashes, and odds ratios that were calculated based on the logistic regression results were used to quantify the association between crash attributes and drivers’ crash involvement in different types of crashes. Results showed that drivers’ involvement patterns in different crash types were affected by different factors, and the involvement patterns differed among the examined age groups. Knowledge generated from the present study could help improve the development of countermeasures for driving safety enhancement.

Highlights

Road traffic crashes are a major challenge to public health [1,2]
As for the influence of time of day, the Odds ratio (OR) for CMVT crashes was the highest during the time period of 12−17 pm (OR = 4.30, p < 0.001), while the OR for crashes with stopped vehicles (CSV) crashes during the time period of 0−5 am was much higher (OR = 10.13, p < 0.001) than all the other time periods
The results reported in [29] confirm that time of day is associated with crash risk, but the differences between different crash types have not been investigated for drivers with different ages

Summary

Introduction

Road traffic crashes are a major challenge to public health [1,2]. As compared to middle-aged experienced drivers, younger drivers have higher violation rates, tend to underestimate the risks of various violations, have a lower level of motivation to follow traffic rules, and are overly involved in running red lights [7,10,11]. These injudicious and risk-taking behaviors are closely associated with increased crash risk [12]. Older drivers experience greater mental workloads than younger drivers due to their age-related decline in cognitive capabilities [14]

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Results

Discussion

Conclusion