Feature extraction and dynamic identification of driving intention adapting to multi-mode emotions

Xiao-Yuan Wang,Hai-Xia Zhao,Qing Xu,Ya-Qi Liu,Jun-Yan Han,Yuan-Yuan Xia,Shi-Jie Liu

doi:10.1177/1687814019839906

Abstract

Accurate identification of driving intention and reasonable control of driver’s behavior is seen as an important mean to reduce man-made traffic accidents for the intelligent vehicle. However, the intention identification processes associated with driving emotion-related impact have received very little attention. With the aim of uncovering the emotional impact on driving intention identification, the car-following condition was taken as an example, and multi-source and dynamic data of human–vehicle–environment under different driving emotional states were obtained through the experiments of emotions induction, actual driving, and virtual driving in this study. The feature extraction and dynamic identification models based on rough set theory and back-propagation artificial neural network were built to recognize driving intentions. The results showed that there were some differences in driving intention identification under different emotional modes. The differences were mainly manifested in the complexit...

Highlights

Traffic accidents constitute a global social and economic problem
The distribution of actual driving test data and identification accuracy of driving intention under different emotional states are shown as Figure 5
The results showed that the feature extraction and dynamic identification models of driving intentions proposed in this article were reasonable and effective

Summary

Introduction

Human factor plays a more important role in the traffic accident beyond vehicle, road, and other factors.[1,2] a particular interest has been shown to drivers’ behaviors research in the domain of traffic safety.[326]. Relevant research showed that 90% of rear-end collisions and 60% of frontal collision could be avoided, if driver realized the danger and took effective measures 1 s in advance.[7,8] it is an important means to control the driving behavior reasonably for the traffic accidents reduction and traffic safety improvement. Driving Safety Alerting (DSA), as an important module of the Advanced Driver Assistance System (ADAS), is one of the effective techniques to prevent factitious traffic accidents.[9] The accurate understanding of the driver’s

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Discussion

Conclusion