Dajana Bartulović’s research while affiliated with University of Zagreb and other places

Today’s airport passenger terminals are required to be planned and designed to ensure flexibility for future adjustments at minimal cost, but also to respond to changes in demand and/or needs of passengers, airlines, and aircraft. To achieve these goals for airports and their operators, planning must be flexible and balanced. Recent data show that the airline business model of low-cost carriers continues to grow, especially after the pandemic. The analysis of the passenger traffic demand and shares of airline business models against the capacity of the existing airport terminal facilities can indicate whether certain adjustments are needed to meet the future conditions. In this research, forecasting of traffic demand and shares of airline business models was made. The forecasting tools of Python and MS Excel were used. Based on traffic demand forecasts and the dominant airline business model, guidelines for future airport terminal planning were proposed for the case-study airport. An example of the adjustment of airport terminal facilities at Pula Airport passenger terminal is provided using AutoCAD, according to forecasted traffic demand and the dominant share of low-cost carriers.

Based on the projected growth in passenger air traffic and the need for better utilization of existing capacities, the level of service (LOS) concept in the design and planning of airport terminal facilities is crucial. By monitoring and quickly responding to expected changes in passengers’ and airlines’ needs, better utilization of airport terminal facilities in the passenger terminal can be achieved. The factors that influence the level of service (LOS) from the passenger perspective were evaluated in order to improve the user experience. Definitions of the level of service, key indicators of customer satisfaction, and a decision-making process using the analytical hierarchy process (AHP) method are described. A survey questionnaire was developed, passengers’ preferences were collected, and an analysis of the results was conducted. A hierarchical AHP decision-making model with associated criteria and sub-criteria was developed to determine the optimal level of service for low-cost carriers. Finally, by using the AHP model, new spatial–temporal parameters for the optimal level of service (LOS) for low-cost carriers (LCCs) are proposed, developed, and presented. The main objective is to adjust the existing LOS concept considering the business characteristics of low-cost carriers, in order to improve the efficiency of airport terminal facilities.

This study examines the causal relationship between air transport demand and socio-economic indicators, with a focus on post-recession recovery dynamics. Using monthly data from 1990 to 2022, the research explores causality between air transport indicators and socio-economic indicators, based on which a temporal causal model for forecasting is created. A temporal causal model, integrating air transport and socio-economic metrics, is introduced to improve passenger air transport forecasting. Forecasted values from the temporal causal model and an ARIMA model were compared with actual realized traffic to assess the quality and accuracy of the models. Based on the comparison, the temporal causal model enables instant analysis of circumstances and causes in dynamic environments, as well as reliable forecasting of upcoming intermediate periods. This research contributes to airlines and other air transport stakeholders by delivering a reliable short-term forecasting tool for informed decision-making and sustainable growth.

In flight operations, the workload settings refer to the shift work, duty time, flight time, number of sectors, rest periods, time of day, duty patterns, number of time-zone transitions, number of consecutive duty days, and changes in the schedule. Workload factors, together with the biological mechanisms (the circadian rhythm, homeostatic sleep pressure, sleep inertia), can lead to the appearance of fatigue. Fatigue affects numerous tasks, such as performing inaccurate flight procedures, missing radio calls, missing or being too slow to pick up system warnings, forgetting or performing routine tasks inaccurately, and others. The focus of this paper is to determine which flight crew workload settings elements impact the appearance of fatigue. The process of collecting data regarding flight crew workload settings and fatigue is conducted on a sample of four airline pilots using an electronic CRD system of standardized chronometric cognitive tests and subjective self-assessment scales. Causal modeling tools of the IBM SPSS Statistics were used to detect correlations among flight crew workload settings, indicators of the subjective perception of fatigue, and measured fatigue indicators. In the final step, a set of simulations was created using simulation tools of the IBM SPSS Statistics to show how modifications of flight crew workload settings, such as modified duty time, number of days off, and others, can impact the level of fatigue. The obtained results can help improve the future planning of flight crew workload set-up and mitigate or prevent the appearance of fatigue in flight operations.

Conducting flight operations at the pace of air traffic relies on shift work, overtime work, work at night, work in different and numerous time zones, and unbalanced flight crew schedules. Such working hours and workload settings can cause disturbances of the circadian rhythm and sleep disorders among flight crew members; this can result in fatigue and can have an impact on the safety of flight operations. Fatigue impacts many cognitive abilities such as vigilance, memory, spatial orientation, learning, problem solving, and decision making. In aviation, fatigue has been identified as a hazard to the safety of flight operations. This paper describes objectivation methods for data collecting processes regarding flight crew fatigue, using an electronic system of standardized chronometric cognitive tests and subjective self-assessment surveys on the subjective perception of fatigue. The data collected were analyzed using statistical methods to identify and quantify elements that affect the appearance of fatigue. Finally, causal modeling methods were used to determine correlations among the measured flight crew fatigue indicators, the subjective perception of fatigue, and the defined workload settings. The results of this research reveal which elements strongly impact flight crew fatigue. The detected correlations can help define improved measures for the mitigation of fatigue risk in future flight operations.

Ergonomics ensures the tools, procedures, and environment that employees use is appropriate to fit the employee’s job requirements and personal capabilities. Ergonomic hazards are situations in workplace that can cause human failure. This can include repetition, awkward posture, forceful motion, stationary position, direct pressure, vibration, extreme temperature, noise, work stress, and other. In aviation, the SHELL model is a conceptual model that defines the relationship between aviation system environment and the human component. Overall goal is to improve human performance with respect to health, safety, and work environment. Performance measurement and risk assessment of any operator in aviation are fundamental to management planning and control activities. To achieve this purpose, safety risk assessment methods are developed and used. This paper provides the overview of safety risk assessment methods in ergonomics such as Systems-Theoretic Process Analysis (STPA) method, the Event Analysis of Systemic Teamwork Broken Links (EAST-BL) method, and the Network Hazard Analysis and Risk Management System (Net-HARMS) method, with the special emphasis on predictive safety risk assessment methods such as Lumbar Motion Monitor Method, the Occupational Repetitive Action (OCRA) Methods (OCRA Index and OCRA Checklist), Systematic Human Error Reduction and Prediction Approach (SHERPA), Task Analysis for Error Identification (TAFEI), the Multiple Resources Time-Sharing Model (MRTSM), the Situational Awareness Global Assessment Technique (SAGAT), and the Adaptive Neuro-Fuzzy Inference Systems (ANFIS). Paper outlines the advantages and applicability of predictive safety risk assessment methods in aviation ergonomics.KeywordsPredictiveSafetyRisk assessment methodsAviationErgonomics

The notion of safety is a very complex set of phenomena within the system that are interconnected in a unique and very complex way. The main objective of any safety management system is to prevent accidents and adverse events, hence safety management system has to be able to process, monitor and improve safety performance of an organization. Aim of the paper is to determine compatibility between aviation and maritime safety management systems through analysis of three top safety management areas, i.e., framework of each safety management system, safety risk management processes, and safety methodologies and performance management. Determining systems' compatibility, opens up the possibility to use certain techniques implemented in aviation safety management and implement them in maritime safety management in order to improve its efficiency.

A predictive safety management methodology implies steps and tools of predictive safety management in aviation, i.e., use of predictive (forecasting) and causal modeling methods to identify potential and possible hazards in the future, as well as their causal factors which can help define timely and efficient mitigation measures to prevent or restrain emerging hazards turning into adverse events. The focus of this paper is to show how predictive analysis of an organization’s safety performance can be conducted, on the sample airport. A case study regarding implementation of predictive analysis of an organization’s safety performance, was performed at Split Airport. The predictive analysis of an airport’s safety performance was conducted through the analysis of Split Airport safety database, causal modeling of Split Airport organizational and safety performance indicators, outlier root cause analysis of Split Airport safety performance indicators, predictive analysis of safety performance (forecasting of Split Airport organizational and safety performance indicators), and scenario cases that simulate future behavior of Split Airport safety performance indicators. Based on detected future hazards, and their causal factors, the appropriate mitigation measures are proposed for the purpose of improving and maintaining an acceptable level of safety at the airport.

Due to the continuous growth of air traffic and the development of aviation systems, the current safety management methodologies should be improved and upgraded. Safety management systems help aviation organizations to manage, maintain and increase safety efficiently. The focus of the research is on the development of the predictive safety management methodology to upgrade current reactive and proactive safety management methodologies and to improve the overall safety level in aviation organizations. Predictive methods are used in various aviation sectors (air navigation services, airport operations, airline operations) for planning purposes but not in the segment of safety management. Available examples of predictive methods were tested and analyzed. Time series decomposition methods were selected as most suited for implementation in aviation safety management. The paper explicitly emphasizes correlations between safety management methodologies in the sample aviation organization. The paper also shows how causal links among organizational and safety performance indicators can be detected, by developing causal models of mutual influences using causal modeling methods, on the sample organization. This research defined steps and tools of the conceptual model of predictive safety management methodology, which enables an organization to identify and mitigate future adverse events.