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Predicting Real-Time Crash Risk for Urban Expressways in China
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-01-30
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
We developed a real-time crash risk prediction model for urban expressways in China in this study.
About two-year crash data and their matching traffic sensor data from the Beijing section of Jingha expressway were utilized for this research.
The traffic data in six 5-minute intervals between 0 and 30 minutes prior to crash occurrence was extracted, respectively.
To obtain the appropriate data training period, the data (in each 5-minute interval) during six different periods was collected as training data, respectively, and the crash risk value under different data conditions was defined.
Then we proposed a new real-time crash risk prediction model using decision tree method and adaptive neural network fuzzy inference system (ANFIS).
By comparing several real-time crash risk prediction methods, it was found that our proposed method had higher precision than others.
And the training error and testing error were minimum (0.280 and 0.291, resp.) when the data during 0 to 30 minutes prior to crash occurrence was collected and the decision tree-ANFIS method was applied to train and establish the real-time crash risk prediction model.
The prediction accuracy of the crash occurrence could reach 65% when 0.60 was considered as the crash prediction threshold.
American Psychological Association (APA)
Liu, Miaomiao& Chen, Yongsheng. 2017. Predicting Real-Time Crash Risk for Urban Expressways in China. Mathematical Problems in Engineering،Vol. 2017, no. 2017, pp.1-10.
https://search.emarefa.net/detail/BIM-1191303
Modern Language Association (MLA)
Liu, Miaomiao& Chen, Yongsheng. Predicting Real-Time Crash Risk for Urban Expressways in China. Mathematical Problems in Engineering No. 2017 (2017), pp.1-10.
https://search.emarefa.net/detail/BIM-1191303
American Medical Association (AMA)
Liu, Miaomiao& Chen, Yongsheng. Predicting Real-Time Crash Risk for Urban Expressways in China. Mathematical Problems in Engineering. 2017. Vol. 2017, no. 2017, pp.1-10.
https://search.emarefa.net/detail/BIM-1191303
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1191303