Biomaterial Database

Association between Crash Attributes and Drivers' Crash Involvement: A Study Based on Police-Reported Crash Data. 2020

Guofa Li, and Weijian Lai, and Xingda Qu

Institute of Human Factors and Ergonomics, College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen 518060, China.

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.

UI	MeSH Term	Description	Entries
D008297	Male		Males
D008875	Middle Aged	An adult aged 45 - 64 years.	Middle Age
D002681	China	A country spanning from central Asia to the Pacific Ocean.	Inner Mongolia,Manchuria,People's Republic of China,Sinkiang,Mainland China
D005260	Female		Females
D006801	Humans	Members of the species Homo sapiens.	Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D000063	Accidents, Traffic	Accidents on streets, roads, and highways involving drivers, passengers, pedestrians, or vehicles. Traffic accidents refer to AUTOMOBILES (passenger cars, buses, and trucks), BICYCLING, and MOTORCYCLES but not OFF-ROAD MOTOR VEHICLES; RAILROADS nor snowmobiles.	Traffic Collisions,Traffic Crashes,Traffic Accidents,Accident, Traffic,Collision, Traffic,Collisions, Traffic,Crashes, Traffic,Traffic Accident,Traffic Collision
D000367	Age Factors	Age as a constituent element or influence contributing to the production of a result. It may be applicable to the cause or the effect of a circumstance. It is used with human or animal concepts but should be differentiated from AGING, a physiological process, and TIME FACTORS which refers only to the passage of time.	Age Reporting,Age Factor,Factor, Age,Factors, Age
D001334	Automobile Driving	The effect of environmental or physiological factors on the driver and driving ability. Included are driving fatigue, and the effect of drugs, disease, and physical disabilities on driving.	Automobile Drivings,Driving, Automobile,Drivings, Automobile
D016015	Logistic Models	Statistical models which describe the relationship between a qualitative dependent variable (that is, one which can take only certain discrete values, such as the presence or absence of a disease) and an independent variable. A common application is in epidemiology for estimating an individual's risk (probability of a disease) as a function of a given risk factor.	Logistic Regression,Logit Models,Models, Logistic,Logistic Model,Logistic Regressions,Logit Model,Model, Logistic,Model, Logit,Models, Logit,Regression, Logistic,Regressions, Logistic
D016495	Police	Agents of the law charged with the responsibility of maintaining and enforcing law and order among the citizenry.	Law Enforcement Officers,Police Force,Police Officers,Enforcement Officer, Law,Enforcement Officers, Law,Law Enforcement Officer,Officer, Law Enforcement,Officer, Police,Officers, Law Enforcement,Officers, Police,Police Forces,Police Officer