Recognizing the situation awareness of forklift operators based on EEG techniques in a field experiment.

Lack of situation awareness (SA) is the primary cause of human errors when operating forklifts, so determining the SA level of the forklift operator is crucial to the safety of forklift operations. An EEG recognition approach of forklift operator SA in actual settings was presented in order to address the issues with invasiveness, subjectivity, and intermittency of existing measuring methods. In this paper, we conducted a field experiment that mimicked a typical forklift operation scenario to verify the differences in EEG states of forklift operators with different SA levels and investigate the correlation of multi-band combination features of each brain region of forklift operators with SA. Based on the sensitive EEG combination indexes, Support Vector Mechanism was used to construct a forklift operator SA recognition model. The results revealed that there were differences between forklift operators with high and low SA in the θ, α, and ß frequency bands in zones F, C, P, and O; combined EEG indicators θ/ß, (α + θ)/(α + ß), and θ/(α + ß) in zones F, P, and C were significantly correlated with SA; the recognition accuracy of the model reached 88.64% in the case of combined EEG indicators of zones C & F & P as input. It could provide a reference for SA measurement, contributing to the improvement of SA.

Investigating the relationship between eye movements and the situation awareness of forklift operators for accident prevention.

This study investigated differences in eye movement indicators among forklift operators with different situation awareness (SA) and the relationship between eye movement indicators and the SA of forklift operators to verify the effectiveness of eye movement tracking in assessing SA and the factors affecting operators' SA for improving forklift operation safety. An eye movement tracking system was used to collect eye movement data from 15 forklift operators while they performed a series of forklift tasks. The SA global assessment technique (SAGAT) was used to determine the SA score of each operator. The results indicated that the fixation duration percentage (FDP), fixation count percentage (FCP) and average fixation duration (AFD) all had a positive relationship with SA in the work-related area of interest (AOI). These findings support eye movement tracking as an effective technique to quantitatively evaluate forklift operators' SA and provide insights into how forklift operators' SA could be improved.

Correlation Evaluation of Pilots' Situation Awareness in Bridge Simulations via Eye-Tracking Technology.

To maintain situation awareness (SA) when exposed to emergencies during pilotage, a pilot needs to selectively allocate attentional resources to perceive critical status information about ships and environments. Although it is important to continuously monitor a pilot's SA, its relationship with attention is still not fully understood in ship pilotage. This study performs bridge simulation experiments that include vessel departure, navigation in the fairway, encounters, poor visibility, and anchoring scenes with 13 pilots (mean = 11.3 and standard deviation = 1.4 of experience). Individuals were divided into two SA group levels based on the Situation Awareness Rating Technology (SART-2) score (mean = 20.13 and standard deviation = 5.83) after the experiments. The visual patterns using different SA groups were examined using heat maps and scan paths based on pilots' fixations and saccade data. The preliminary visual analyses of the heat maps and scan paths indicate that the pilots' attentional distribution is modulated by the SA level. That is, the most concerning areas of interest (AOIs) for pilots in the high and low SA groups are outside the window (AOI-2) and electronic charts (AOI-1), respectively. Subsequently, permutation simulations were utilized to identify statistical differences between the pilots' eye-tracking metrics and SA. The results of the statistical analyses show that the fixation and saccade metrics are affected by the SA level in different AOIs across the five scenes, which confirms the findings of previous studies. In encounter scenes, the pilots' SA level is correlated with the fixation and saccade metrics: fixation count (p = 0.034 < 0.05 in AOI-1 and p = 0.032 < 0.05 in AOI-2), fixation duration (p = 0.043 < 0.05 in AOI-1 and p = 0.014 < 0.05 in AOI-2), and saccade count (p = 0.086 < 0.1 in AOI-1 and p = 0.054 < 0.1 in AOI-2). This was determined by the fixation count (p = 0.024 < 0.05 in AOI-1 and p = 0.034 < 0.05 in AOI-2), fixation duration (p = 0.036 < 0.05 in AOI-1 and p = 0.047 < 0.05 in AOI-2), and saccade duration (p = 0.05 ≤ 0.05 in AOI-1 and p = 0.042 < 0.05 in AOI-2) in poor-visibility scenes. In the remaining scenes, the SA could not be measured using eye movements alone. This study lays a foundation for the cognitive mechanism recognition of pilots based on SA via eye-tracking technology, which provides a reference to establish cognitive competency standards in preliminary pilot screenings.

Identifying Cognitive Mechanism Underlying Situation Awareness of Pilots' Unsafe Behaviors Using Quantitative Modeling.

Situation awareness (SA) of pilots' unsafe behavior can ensure safety onboard. Thus, the cognitive mechanism that controls the SA leading to unsafe behavior must be articulated. This study employs the SA model and theory of planned behavior (TPB) to articulate a quantitative model of ship safe piloting. Firstly, the hierarchical classification framework of unsafe behaviors was constructed as an analytical foundation for rational and unconscious behaviors in sight of cognitive processes, and then the measurement elements of the cognitive mechanisms for behaviors were identified. Subsequently, based on the structural model, a hypothetical model of the cognitive path for unsafe behaviors was proposed by using the extended TPB, where there are four independent variables (i.e., attitude (ATD), subjective norm (SN), and perceived behavioral control (PBC)), one mediating variables (i.e., SA) and two dependent variables (i.e., behavioral intention (BI) and unsafe behaviors (BE)). Finally, this hypothetical model was analyzed with the data resources from extended TPB questionnaire of 295 pilots. Analysis results show that relationships of causation and mediation in the cognitive mechanism are in line with the behavior pattern and SA have a pronounced mediating effect and a strong relevance to the causal chain of extended TPB framework. This study integrated the SA three-level model to understand the motivation-cognition-action-feedback (MCAF) mechanism of pilots' unsafe behaviors under cognitive mode of information processing through structural model. It would make a valuable contribution to the assessment and intervention of safety behaviors, and provide a basic framework for monitoring the situation awareness of pilot by man-machine interactive measurement technology in the future.