Estimating Rear-End Accident Probabilities with Different Driving Tendencies at Signalized Intersections in China
Joint Authors
Li, Yaping
Wan, Qian
Li, Yingshuai
Wang, Weijie
Lu, Jian
Source
Journal of Advanced Transportation
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-01-20
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Rear-end accidents are the most common accident type at signalized intersections because of the different driving tendencies in the dilemma zone (DZ), where drivers are faced with indecisiveness of making “stop or go” decisions at yellow onset.
In various researches, the number of vehicles in the DZ has been used as a safety indicator—the more the vehicles in the DZ, the higher the probability of rear-end accidents.
However, the DZ-associated rear-end accident potential varies depending on drivers’ driving tendencies and the situations (position and speed) at the yellow onset.
This study’s primary objective is to explore how the driving tendency impacts the DZ distribution and the probability of rear-end accidents.
To achieve this, three types of driving tendencies were classified using K-means clustering analysis based on driving variables.
Further, the boundary of the DZ is determined by logistic regression model of drivers’ stop/go decision.
Then, we proposed the conditional probability model of rear-end accidents and developed a Monte Carlo simulation framework to calculate the model.
The results indicate that the rear-end accident probability is dependent on the driving tendency even at the same position with the same speed in the DZ.
The aggressive type has the highest risk probability followed by conservative and then the normal types.
The quantitative results of the study can provide the basis for rear-end accident assessments.
American Psychological Association (APA)
Wang, Weijie& Li, Yingshuai& Lu, Jian& Li, Yaping& Wan, Qian. 2019. Estimating Rear-End Accident Probabilities with Different Driving Tendencies at Signalized Intersections in China. Journal of Advanced Transportation،Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1169907
Modern Language Association (MLA)
Wang, Weijie…[et al.]. Estimating Rear-End Accident Probabilities with Different Driving Tendencies at Signalized Intersections in China. Journal of Advanced Transportation No. 2019 (2019), pp.1-11.
https://search.emarefa.net/detail/BIM-1169907
American Medical Association (AMA)
Wang, Weijie& Li, Yingshuai& Lu, Jian& Li, Yaping& Wan, Qian. Estimating Rear-End Accident Probabilities with Different Driving Tendencies at Signalized Intersections in China. Journal of Advanced Transportation. 2019. Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1169907
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1169907