Rapid Driving Style Recognition in Car-Following Using Machine Learning and Vehicle Trajectory Data
Joint Authors
Lu, Jian
Xue, Qingwen
Wang, Ke
Liu, Yujie
Source
Journal of Advanced Transportation
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-01-23
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Rear-end collision crash is one of the most common accidents on the road.
Accurate driving style recognition considering rear-end collision risk is crucial to design useful driver assistance systems and vehicle control systems.
The purpose of this study is to develop a driving style recognition method based on vehicle trajectory data extracted from the surveillance video.
First, three rear-end collision surrogates, Inversed Time to Collision (ITTC), Time-Headway (THW), and Modified Margin to Collision (MMTC), are selected to evaluate the collision risk level of vehicle trajectory for each driver.
The driving style of each driver in training data is labelled based on their collision risk level using K-mean algorithm.
Then, the driving style recognition model’s inputs are extracted from vehicle trajectory features, including acceleration, relative speed, and relative distance, using Discrete Fourier Transform (DFT), Discrete Wavelet Transform (DWT), and statistical method to facilitate the driving style recognition.
Finally, Supporting Vector Machine (SVM) is applied to recognize driving style based on the labelled data.
The performance of Random Forest (RF), K-Nearest Neighbor (KNN), and Multi-Layer Perceptron (MLP) is also compared with SVM.
The results show that SVM overperforms others with 91.7% accuracy with DWT feature extraction method.
American Psychological Association (APA)
Xue, Qingwen& Wang, Ke& Lu, Jian& Liu, Yujie. 2019. Rapid Driving Style Recognition in Car-Following Using Machine Learning and Vehicle Trajectory Data. Journal of Advanced Transportation،Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1170283
Modern Language Association (MLA)
Xue, Qingwen…[et al.]. Rapid Driving Style Recognition in Car-Following Using Machine Learning and Vehicle Trajectory Data. Journal of Advanced Transportation No. 2019 (2019), pp.1-11.
https://search.emarefa.net/detail/BIM-1170283
American Medical Association (AMA)
Xue, Qingwen& Wang, Ke& Lu, Jian& Liu, Yujie. Rapid Driving Style Recognition in Car-Following Using Machine Learning and Vehicle Trajectory Data. Journal of Advanced Transportation. 2019. Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1170283
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1170283