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Improvement of Highway Safety I: Identification of Causal Factors Through Fault‐Tree Modeling 1
Author(s) -
Kuzminski P.,
Eisele J. S.,
Garber N.,
Schwing R.,
Haimes Y. Y.,
Li D.,
Chowdhury M.
Publication year - 1995
Publication title -
risk analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.972
H-Index - 130
eISSN - 1539-6924
pISSN - 0272-4332
DOI - 10.1111/j.1539-6924.1995.tb00323.x
Subject(s) - fault tree analysis , causation , identification (biology) , tree (set theory) , accident (philosophy) , representation (politics) , crash , computer science , fault (geology) , engineering , data mining , reliability engineering , mathematics , mathematical analysis , philosophy , botany , epistemology , seismology , politics , political science , law , biology , programming language , geology
As the first article of a two‐part series, the purpose of this paper is to examine the functional factors that contribute to automobile accident occurrence and to model the causation structure in the form of a fault‐tree. The fault‐tree model provides an intuitive framework for qualitatively decomposing possible pathways to accident occurrence. Fault‐tree analysis also provides a statistical representation of how interacting driver, vehicle, and environmental factors contribute to the likelihood of automobile accident occurrence. The application of this model facilitates pinpointing those factors that most contribute to accident causation and subsequently enables the identification and comparison of potential crash avoidance technologies.