TY - GEN
T1 - Analysis of Vehicle Driving Styles at Freeway Merging Areas Using Trajectory Data
AU - Wen, Shuai
AU - Shahd Omar, Xin Gu
AU - Jin, Xi
AU - He, Zhengbing
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Driving style is a comprehensive representation of the driver's internal psychological factors as well as external environmental and traffic management factors. Identifying driving styles can help suggest targeted management strategies and personalized active safety and autonomous driving strategies. This paper analyzes the drivers' driving styles according to the vehicle trajectory data from unmanned aerial vehicle (UAV) videos. Nine characteristic indexes from two aspects of drivers themselves and their interaction with the surrounding vehicles are extracted. The principal component analysis and K-means clustering method are used to reduce the index dimensionality and classify the driving styles of merging vehicles. The results show that the drivers' driving styles could be classified into four categories: aggressive, relatively aggressive, relatively cautious, and cautious. The analysis of the characteristics of different driving styles shows that it is feasible to classify driving styles based on trajectory data.
AB - Driving style is a comprehensive representation of the driver's internal psychological factors as well as external environmental and traffic management factors. Identifying driving styles can help suggest targeted management strategies and personalized active safety and autonomous driving strategies. This paper analyzes the drivers' driving styles according to the vehicle trajectory data from unmanned aerial vehicle (UAV) videos. Nine characteristic indexes from two aspects of drivers themselves and their interaction with the surrounding vehicles are extracted. The principal component analysis and K-means clustering method are used to reduce the index dimensionality and classify the driving styles of merging vehicles. The results show that the drivers' driving styles could be classified into four categories: aggressive, relatively aggressive, relatively cautious, and cautious. The analysis of the characteristics of different driving styles shows that it is feasible to classify driving styles based on trajectory data.
UR - https://www.scopus.com/pages/publications/85141852303
U2 - 10.1109/ITSC55140.2022.9922336
DO - 10.1109/ITSC55140.2022.9922336
M3 - Conference contribution
AN - SCOPUS:85141852303
T3 - IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
SP - 3652
EP - 3656
BT - 2022 IEEE 25th International Conference on Intelligent Transportation Systems, ITSC 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 25th IEEE International Conference on Intelligent Transportation Systems, ITSC 2022
Y2 - 8 October 2022 through 12 October 2022
ER -