Identification of Stress State for Drivers Under Different GPS Navigation Modes

IEEE Access

卷:8

Beom-Seok Oh¹  Jiahui Lv²  Jingbin Li²  Ya Jun Yu²  Zhiping Lin³ 

[1] Department of Computer Science, Gyeongsang National University, Jinju, South Korea;

[2] Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, China;

[3] School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore;

关键词: Driver stress;    GPS navigation;    k-NN classifier;    Stroop color word test;    HRV features;    ECG signal;   

DOI  :  10.1109/ACCESS.2020.2998156

来源: DOAJ

【 摘 要 】

It is commonly known that Global Positioning System (GPS) can alleviate travelling difficulties of automobile drivers, and generally we hold the view that it reduces the driver's stress when they are in unfamiliar road conditions. In this research, an in-laboratory experiment and an in-car experiment are conducted to find out whether GPS instructions can reduce or may induce additional mental stress of drivers. Electrocardiography (ECG) signals are collected in the experiments and the extracted heart rate variability (HRV) features are used for analysis. Three binary classifiers, specifically Support Vector Machine, k-Nearest Neighbor (k-NN) and Random Forest, are trained based on the data collected in the in-laboratory experiment, where the stress state is elicited by the Stroop color word Test. The k-NN classifier outperforms the other two classifiers, and thus is applied to the data collected in the in-car experiment, to identify drivers' stress state under different driving events, such as waiting for traffic lights, turning, under GPS instructions, and traffic conditions like overtaking, or changing lanes. During each event, whether the driver is in stress or relaxed state for each time instant is predicted based on the trained classifier. The percentages of time that the driver is in stress state for each type of events are computed. It shows that GPS instructions cause the second largest time-percentage of stress state, lower than that caused by the turning event, but higher than that caused by the events of waiting for traffic lights and other traffic conditions.

【 授权许可】

Unknown