How Do Captains Keep Their Bearings in Waterway Tunnels?

Waterway tunnels are like long, dark corridors beneath mountains where ships must move without a visible horizon. This peculiarity can raise stress and mental fatigue for bridge officers, affecting their decisions. To investigate, Chinese researchers recreated a typical tunnel environment using a ship maneuvering simulator. During the trials, they recorded brain (EEG) and heart (ECG) signals of captains, observing how they change over time and space. The data showed that as tunnel length increases, cognitive load – the amount of information the brain must process – also rises. Researchers turned these findings into a mathematical model that quantifies officers' cognitive load. Then, applying the entropy‑weight TOPSIS method, they assessed navigation risk in tunnels of various lengths, pinpointing the most hazardous sections. The outcome is a visual map highlighting critical points, giving authorities a concrete tool to boost safety. In practice, knowing when and where the brain gets fatigued allows interventions such as warning signals, better lighting, or operational breaks, reducing accident risk in waterway tunnels.

Cognitive load was assessed through spectral analysis of EEG signals, focusing on alpha (8‑12 Hz) and theta (4‑7 Hz) bands, typical of relaxed wakefulness and sustained attention. An increase in theta power and a decrease in alpha were interpreted as markers of higher mental effort. Simultaneously, ECG data were examined for heart rate (HR) and heart rate variability (HRV) changes, parameters sensitive to autonomic stress. Researchers synchronized physiological data with simulation events (turns, acceleration, reduced visibility) to build a temporal response matrix. Using multivariate linear regressions, they identified the most predictive variables of cognitive load, integrating them into a logistic regression model that estimates the probability of decision error. For risk assessment, the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method was enhanced with weights calculated via Shannon entropy, ensuring that the most variable indicators (e.g., tunnel length, simulated traffic density) exerted greater influence on the final ranking. Results visualization employed 3D GIS, overlaying high‑risk zones onto tunnel topographic maps, facilitating interventions by engineers and maritime traffic controllers.