Abstract
A classification and recognition method for the severity of road traffic accident based on rough set theory and support vector machine was proposed in this article. Rough set theory was used to cal...
Highlights
With the increasing of road traffic infrastructures, motor vehicles, drivers, and traffic flow, the role of road traffic in supporting and guiding economic and social development is becoming more and more obvious
Yau,4 with the use of logit model, a population-based casecontrol study was conducted to examine the factors, which affected the severity of single vehicle traffic accident in Hong Kong
The results showed that intelligent classification model had higher classification accuracy and generalization. (e.g. Xie et al.12 compared three models of back-propagation neural network (BPNN), Bayesian neural network (BNN), and negative binomial (NB) regression model using the data collected from rural street-front roads in Texas
Summary
With the increasing of road traffic infrastructures, motor vehicles, drivers, and traffic flow, the role of road traffic in supporting and guiding economic and social development is becoming more and more obvious. With the use of logit model, a population-based casecontrol study was conducted to examine the factors, which affected the severity of single vehicle traffic accident in Hong Kong. Ma et al. used logit model to study the influencing factors of the severity of road tunnel accident They studied road safety evaluation based on accident severity by using fuzzy Delphi method. (e.g. Xie et al. compared three models of back-propagation neural network (BPNN), Bayesian neural network (BNN), and negative binomial (NB) regression model using the data collected from rural street-front roads in Texas. They evaluated the application of BNN model in vehicle collision prediction. The method could optimize and simplify the input of classification and recognition model, improving the calculation speed and classification accuracy of the model
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