The conceptual framework for assessing the situational awareness (SA) of drivers consists of three hierarchical levels: perception of the elements of the environment, comprehension of the elements, and decision-making in the near future. A common challenge in evaluating SA is the determination of the available subjective and objective techniques and their selection and integration into methodologies. Among the objective techniques, eye tracking is commonly used, considering the influence of gaze behavior on driving. This review is presented as an innovative approach to the subject matter, introducing physiological metrics based on eye tracking and investigating their application in assessing the SA of drivers. In addition, experiments and methodologies that revealed patterns at the three levels of SA were identified. For this purpose, databases were searched, and 38 papers were considered. Articles were clustered according to prevalent themes such as eye-tracking metrics, eye-tracking devices, experiment design, and the relationship between SA and eye-tracking. This review summarizes the main metrics and key findings for each article and reveals a wide relationship between the eye-tracking metrics and SA. The influence of appropriately calibrated equipment, refined data collection protocols, and adequate selection of the eye-tracking metrics was examined. Further reviews are needed to systematically collect more evidence.

Background: This study explores forklift operators’ situational awareness (SA) and human errors in logistic operations using a multiphase approach as an innovative methodology. Methods: Ethnography, eye tracking, error taxonomy, and retrospective think-aloud (RTA) were used to study the diverse cognitive, behavioral, and operational aspects affecting SA. After analyzing 566 events across 18 tasks, this research highlighted eye tracking’s potential by offering real-time insights into operator behavior and RTA’s potential as a method for cross-checking the causal factors underlying errors. Results: Critical tasks, like positioning forklifts and lowering pallets, significantly impact incident occurrence, while high-cognitive demand tasks, such as hoisting and identifying pedestrians/obstacles, reduce SA and increase errors. Driving tasks are particularly vulnerable to errors and are the most affected by operator risk generators (ORGs), representing 42% of incident risk events. This study identifies driving, hoisting, and lowering loads as the tasks most influenced by system factors. Limitations include the task difficulty levels, managing physical risk, and training. Future research is suggested in autonomous industrial vehicles and advanced driver assistance systems (ADASs). Conclusions: This study provides valuable insights into how we may improve safety in logistics operations by proposing a multiphase methodology to uncover the patterns of attention, perception, and cognitive errors and their impact on decision-making.

Introducción: Este documento desarrolla un enfoque pionero sobre los factores humanos de las operaciones semimecanizadas de selección, las cuales se abordan desde una perspectiva cognitiva. Materiales y métodos: El modelo aportado se establece a través de una metodología cualitativa, la cual, a partir de varias teorías, es articulada y aplicada a la situación real de una operación de selección (picking semi) mecanizada de una empresa de alimentos secos. Resultados: Los resultados combinan la arquitectura cognitiva de la operación y sus relaciones con factores logísticos, para disminuir el error humano y, por lo tanto, aumentar el nivel de servicio.

Objective: Designing a CPFR (collaborative planning forecasting and replenishment) model for the delivery of diabetes and arterial hypertension medicines from a health insurance company (EPS) to a healthcare provider (IPS) and comparing the performance of this collaborative chain to that of the traditional one through their corresponding supply chain costs. Methodology: A series of collaboration agreements involved in joint planning were established according to the designed CPFR model. This allowed (i) raising the levels of interaction between the health insurance company, the healthcare provider, the supplying pharmaceutical laboratories, and the patients; (ii) determining demand forecasts; (iii) locating distribution centers; and (iv) defining medicine distribution strategies oriented to the minimization of costs along the chain. Subsequently, the main differences between the current operation and CPFR models at the level of structure and decisions were characterized and then evaluated in terms of supply chain costs. Results: The significant impact of the proposed model is demonstrated. The total monthly cost of operating the chain is reduced by 11.2 % on average. Within the proposed innovation, an outstanding place is held by the savings reached in the purchase and distribution of medicines from the laboratory to the distribution centers, and by the customer satisfaction differences, which increased 15.3 % on average during the studied six-month period.