Enhanced Clustering and Comprehensive Scoring Based Driver Behavior Safety Assessment Method Chongqing Jiaotong University

Format:

Book

Conference/Event

Author/Creator:

Sun, Bowen, author.

Contributor:

Lihong, Xia

Mao, Qing

Wen, Long'en

Yi, Zhenxing

Zhan, Zhenfei

Conference Name:

SAE 2023 Intelligent and Connected Vehicles Symposium (2023-09-22 : Nanchang, China)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2023

Summary:

Most traffic accidents are caused by the driving behavior of drivers, so the study of driving behavior plays an important role in traffic safety. In this paper, we propose a comprehensive system for evaluating driver driving behavior safety, including classification and prediction of driver driving styles, as well as comprehensive scoring of driving behaviors. The driving behavior dataset needs to be pre-processed first. After that, we extracted driving behaviors and indicators, and performed cluster analysis on the reconstructed data to obtain three styles: conservative, aggressive, and impatient. We introduced a BP neural network to predict driving styles and obtained a relatively high prediction accuracy. Finally, we calculated the combined subjective and objective weights of the five behaviors and combined them with the developed scoring function to evaluate the driving safety of all drivers with a comprehensive score. The result was the selection of three driving behaviors that need priority attention and training

Notes:

Vendor supplied data

Publisher Number:

2023-01-7069

Access Restriction:

Restricted for use by site license