Abstract:

To explore the changing characteristics of driving load under the construction environment of underground tunnels, a test platform was built, and a driving simulation test was carried out in the construction environment of underground tunnels to obtain the driver's eye movement and ECG data. Taking the time domain index of heart rate, heart rate variability(HRV) and average number of blinks frequency(BF) as parameters, a comprehensive evaluation model of driving load based on factor analysis and entropy was constructed, and a classification method of driving load based on K-means clustering algorithm was proposed. The results show that in the relatively monotonous environment of non-construction sections in underground tunnels, psychological pressure could more accurately reflect the driving load compared to visual pressure. However, in the complex and changeable environment of construction section, psychological pressure is prone to being influenced by driving operations. Moreover, when line of sight is limited, a single visual pressure indicator tends to overestimate the driving load. The comprehensive evaluation model of driving load based on eye movement and ECG exhibits high sensitivity and good stability, and can correct the evaluation results of a single indicator and effectively quantify driving load.

Key words: eye movement, electrocardiogram(ECG), underground tunnel, driving load, construction environment