Decision Tree-Based Maneuver Prediction for Driver Rear-End Risk-Avoidance Behaviors in Cut-In Scenarios
Joint Authors
Cheng, Bo
Wang, Wenjun
Li, Guofa
Hu, Manjiang
Liao, Yuan
Chen, Fang
Source
Journal of Advanced Transportation
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-02-15
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
Predicting driver rear-end risk-avoidance maneuvers in cut-in scenarios, especially dangerous precrash scenarios, benefits the customization of automatic driving, particularly automatic steering.
This paper studies driver rear-end risk-avoidance behaviors in cut-in scenarios on a straight three-lane highway.
Data from 24 participants in 1326 valid trials were collected using a motion-based driving simulator.
An Eysenck Personality Questionnaire (revised for Chinese participants) was used to obtain the personality traits of the participants.
Based on a statistical analysis, the candidate features used in the driver maneuver prediction were determined as a combination of objective risk indicators and driver characteristics.
A decision tree-based model was constructed for maneuver prediction in cut-in scenarios.
The prediction accuracy of the extracted classification rules was 79.2% for the training data set and 80.3% for the test data set.
The most powerful predictive variables were extracted, and their effects on maneuver decisions were analyzed.
The results show that driver characteristics strongly influence the prediction of maneuver decisions.
American Psychological Association (APA)
Hu, Manjiang& Liao, Yuan& Wang, Wenjun& Li, Guofa& Cheng, Bo& Chen, Fang. 2017. Decision Tree-Based Maneuver Prediction for Driver Rear-End Risk-Avoidance Behaviors in Cut-In Scenarios. Journal of Advanced Transportation،Vol. 2017, no. 2017, pp.1-12.
https://search.emarefa.net/detail/BIM-1170928
Modern Language Association (MLA)
Hu, Manjiang…[et al.]. Decision Tree-Based Maneuver Prediction for Driver Rear-End Risk-Avoidance Behaviors in Cut-In Scenarios. Journal of Advanced Transportation No. 2017 (2017), pp.1-12.
https://search.emarefa.net/detail/BIM-1170928
American Medical Association (AMA)
Hu, Manjiang& Liao, Yuan& Wang, Wenjun& Li, Guofa& Cheng, Bo& Chen, Fang. Decision Tree-Based Maneuver Prediction for Driver Rear-End Risk-Avoidance Behaviors in Cut-In Scenarios. Journal of Advanced Transportation. 2017. Vol. 2017, no. 2017, pp.1-12.
https://search.emarefa.net/detail/BIM-1170928
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1170928