Pattern recognition for road traffic accident severity in korea

So Young Sohn, Hyungwon Shin

Research output: Contribution to journalArticlepeer-review

86 Citations (Scopus)


An increasing number of road traffic accidents (RTA) in Korea has emerged as being harmful both for the economy and for safety. An accurately estimated classification model for several severity types of RTA as a function of related factors provides crucial information for the prevention of potential accidents. Here, three data-mining techniques (neural network, logistic regression, decision tree) are used to select a set of influential factors and to build up classification models for accident severity. The three approaches are then compared in terms of classification accuracy. The finding is that accuracy does not differ significantly for each model and that the protective device is the most important factor in the accident severity variation.

Original languageEnglish
Pages (from-to)107-117
Number of pages11
Issue number1
Publication statusPublished - 2001 Jan 1

All Science Journal Classification (ASJC) codes

  • Human Factors and Ergonomics
  • Physical Therapy, Sports Therapy and Rehabilitation


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