A Bayesian Network Approach to Causation Analysis of Road Accidents Using Netica
Joint Authors
Source
Journal of Advanced Transportation
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-18, 18 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-12-12
Country of Publication
Egypt
No. of Pages
18
Main Subjects
Abstract EN
Based on an overall consideration of factors affecting road safety evaluations, the Bayesian network theory based on probability risk analysis was applied to the causation analysis of road accidents.
By taking Adelaide Central Business District (CBD) in South Australia as a case, the Bayesian network structure was established by integrating K2 algorithm with experts’ knowledge, and Expectation-Maximization algorithm that could process missing data was adopted to conduct the parameter learning in Netica, thereby establishing the Bayesian network model for the causation analysis of road accidents.
Then Netica was used to carry out posterior probability reasoning, the most probable explanation, and inferential analysis.
The results showed that the Bayesian network model could effectively explore the complex logical relation in road accidents and express the uncertain relation among related variables.
The model not only can quantitatively predict the probability of an accident in certain road traffic condition but also can find the key reasons and the most unfavorable state combination which leads to the occurrence of an accident.
The results of the study can provide theoretical support for urban road management authorities to thoroughly analyse the induction factors of road accidents and then establish basis in improving the safety performance of the urban road traffic system.
American Psychological Association (APA)
Zou, Xin& Yue, Wen Long. 2017. A Bayesian Network Approach to Causation Analysis of Road Accidents Using Netica. Journal of Advanced Transportation،Vol. 2017, no. 2017, pp.1-18.
https://search.emarefa.net/detail/BIM-1170570
Modern Language Association (MLA)
Zou, Xin& Yue, Wen Long. A Bayesian Network Approach to Causation Analysis of Road Accidents Using Netica. Journal of Advanced Transportation No. 2017 (2017), pp.1-18.
https://search.emarefa.net/detail/BIM-1170570
American Medical Association (AMA)
Zou, Xin& Yue, Wen Long. A Bayesian Network Approach to Causation Analysis of Road Accidents Using Netica. Journal of Advanced Transportation. 2017. Vol. 2017, no. 2017, pp.1-18.
https://search.emarefa.net/detail/BIM-1170570
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1170570