Article
Engineering, Aerospace
Jing Yang, Hongyu Yang, Zhengyuan Wu, Xiping Wu
Summary: Due to increased air traffic flow, air traffic controllers (ATCs) often operate under high workload or even overload, affecting the reliability and efficiency of their commands. This study proposes a method using speech parameters to assess cognitive load in ATCs, based on a comprehensive comparison of existing assessment methods. The proposed model, SCNN-TransE, combines a stacked convolutional neural network (CNN) and the Transformer encoder to capture spatial and temporal features from speech data. Experimental results show that SCNN-TransE outperforms other models in terms of detection accuracy and F1 score, achieving 97.48% and 97.07% respectively. Thus, the proposed model effectively evaluates cognitive load levels.
Article
Engineering, Aerospace
Raquel Garcia, Juan Albarran, Adrian Fabio, Fernando Celorrio, Carlos Pinto de Oliveira, Cristina Barcena
Summary: In the air traffic management environment, air traffic controllers and flight crews communicate via voice using speech recognition to improve situational awareness and safety. This paper presents the work being done to develop ASR models for callsign recognition and highlights the need for partial recognition and improved phonetization to enhance recognition rates.
Article
Engineering, Aerospace
Adan Ernesto Vela, William Singhose, Karen Feigh, John-Paul Clarke, Eric Feron
Summary: This paper examines the potential workload implications of introducing advisory conflict-detection and resolution tools by evaluating how the underlying protocol of a conflict-resolution tool affects the controller taskload. The research shows significant flexibility in the design of conflict-resolution algorithms supporting an advisory system.
CHINESE JOURNAL OF AERONAUTICS
(2021)
Article
Engineering, Industrial
Sepideh Hedayati, Vahid Sadeghi-Firoozabadi, Morteza Bagheri, Mahmoud Heidari, N. N. Sze
Summary: This study evaluated the impact of cognitive functions and personality traits on human error in air traffic controllers. Results showed that error-free controllers scored higher in situational awareness and sustained attention, with no differences in short-term memory and planning ability. In terms of personality traits, controllers with error history differed from those without error history.
Article
Engineering, Aerospace
Maria Zamarreno Suarez, Rosa Maria Arnaldo Valdes, Francisco Perez Moreno, Raquel Delgado-Aguilera Jurado, Patricia Maria Lopez de Frutos, Victor Fernando Gomez Comendador
Summary: The study of human factors in aviation contributes significantly to safety, especially with the use of real-time simulations. The CRITERIA project aims to establish capacity models and investigate the influence of air traffic control events on the workload of air traffic controllers. This paper presents a methodology for defining taskload during simulations and provides recommendations for future research.
Article
Engineering, Multidisciplinary
Yanjun Wang, Liwei Wang, Siyuan Lin, Wei Cong, Jianfei Xue, Washington Ochieng
Summary: Eye movement is a crucial indicator of information-seeking behavior and cognitive strategy for decision-making. The study shows that working experience significantly impacts eye movement patterns in air traffic controllers, with experienced controllers utilizing more efficient search strategies compared to novices.
Article
Ergonomics
Gholam Abbas Shirali, Maryam Malekzadeh
Summary: The study explored human error in an airport control tower through the TRACEr and CARA methods, finding that errors in selection and quality, memory, distraction, and traffic had the highest percentage rates. Emergency situation management had the highest probability of error. This research is the first to classify and quantify human errors in ATC using these methods.
INTERNATIONAL JOURNAL OF OCCUPATIONAL SAFETY AND ERGONOMICS
(2021)
Article
Computer Science, Artificial Intelligence
Yutian Pang, Jueming Hu, Christopher S. Lieber, Nancy J. Cooke, Yongming Liu
Summary: This paper reviews research on air traffic controller workload and proposes a graph-based deep-learning framework with conformal prediction to accurately predict workload levels.
ADVANCED ENGINEERING INFORMATICS
(2023)
Article
Green & Sustainable Science & Technology
Sarka Hoskova-Mayerova, Jan Kalvoda, Miloslav Bauer, Pavlina Rackova
Summary: With the increase in civil aviation traffic and military operations, there is a need for higher airspace throughput and workload for military air traffic controllers. To assess their workload objectively, it is important to set the maximum level of workload that can be required. Measuring the workload based on the complexity and density of air traffic, as done in civil air traffic control, is not suitable for military air traffic control due to the different nature of military flight activities. A method for determining the difficulty of individual air traffic control activities and calculating the workload is proposed.
Article
Engineering, Aerospace
Oliver Ohneiser, Hartmut Helmke, Shruthi Shetty, Matthias Kleinert, Heiko Ehr, Sebastian Schier-Morgenthal, Saeed Sarfjoo, Petr Motlicek, Sarunas Murauskas, Tomas Pagirys, Haris Usanovic, Mirta Mestrovic, Aneta Cerna
Summary: Assistant Based Speech Recognition (ABSR) systems have the potential to reduce air traffic controllers' workload in air traffic control radiotelephony communication. This study investigates how ABSR could support air traffic controllers in a tower environment. The results show that ABSR system, with a command recognition rate of 82.9% and a callsign recognition rate of 94.2%, can reduce workload and improve usability.
Article
Mathematical & Computational Biology
Jie Ren, Shiru Qu, Lili Wang, Yu Wang
Summary: This paper proposes a process model for en route air traffic control from the perspective of operation requirements. By optimizing objectives and constraints, designing algorithms and establishing the model, it aims to improve the performance of air traffic management and enhance the capacity of en route air traffic. The model considers the entire process of air traffic control instructions and uses historical trajectory data as key parameters, demonstrating innovation and effectiveness.
MATHEMATICAL BIOSCIENCES AND ENGINEERING
(2022)
Article
Environmental Sciences
Hengchuan Zhang, Yingying Chen, Ruyu Ni, Yawen Cao, Wenbin Fang, Wan Hu, Guixia Pan
Summary: The study aimed to investigate the joint effects of traffic-related air pollution (TRAP) and healthy lifestyles on cognition among the Chinese elderly. The results showed that participants living > 300 m from major roadways and adopting a healthy lifestyle had a significantly decreased risk of cognitive impairment compared to those living < 50 m from major roadways and adopting an unhealthy lifestyle. Stratified analysis indicated that the impact of TRAP on cognitive impairment was more pronounced among participants adopting an unhealthy lifestyle.
ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY
(2023)
Article
Engineering, Aerospace
Han Yun-Xiang, Huang Xiao-Qiong
Summary: This article establishes a system model for the terminal control area considering constraints between different departure routes, using dioid algebra to describe concurrent events and define interactions between flight trajectories. By introducing a new optimization model and solution, the operational effectiveness of air traffic flow is improved. Different scenarios are presented to demonstrate the performance of the system model in allocating optimal time slots to flights from different airports.
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Martijn IJtsma, Clark Borst, Marinus M. van Paassen, Max Mulder
Summary: Air traffic controller workload is a limiting factor in the current air traffic management system. Adaptive support systems have the potential to balance controller workload and gain acceptance. However, research findings suggest that adaptive support at the level of decision-making may be problematic in complex work environments if human intent cannot be accurately inferred.
IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS
(2022)
Article
Psychology, Applied
Damien Mouratille, Franck Amadieu, Nadine Matton
Summary: This psychometric meta-analysis examines the relationship between cognitive and non-cognitive factors and the training success of Air Traffic Controllers. The results suggest that cognitive factors have a moderate effect, particularly quantitative knowledge, processing speed, work samples, short-term working memory, cognitive composite, and visuo-spatial processing predictors. In contrast, non-cognitive factors have a smaller effect, with only non-cognitive composites and education showing a significant influence on training success. The findings indicate the importance of prioritizing cognitive predictors or alternative assessment methods in the selection processes for Air Traffic Controllers.
JOURNAL OF VOCATIONAL BEHAVIOR
(2022)
Article
Engineering, Industrial
Linda J. Bellamy, Martin Damen, Henk Jan Manuel, Olga N. Aneziris, Ioannis A. Papazoglou, Joy I. H. Oh
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2015)
Article
Public, Environmental & Occupational Health
Ioannis A. Papazoglou, Olga Aneziris, Linda Bellamy, B. J. M. Ale, Joy I. H. Oh
Article
Engineering, Industrial
O. N. Aneziris, I. A. Papazoglou, A. Psinias
Article
Environmental Sciences
C. Pappas, A. Ikonomopoulos, A. Sfetsos, S. Andronopoulos, O. Aneziris, M. Varvayanni, N. Catsaros
Article
Engineering, Industrial
I. A. Papazoglou, O. N. Aneziris, L. J. Bellamy, B. J. M. Ale, J. Oh
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2017)
Article
Engineering, Industrial
I. A. Papazoglou, O. N. Aneziris, L. J. Bellamy, B. J. M. Ale, J. Oh
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2017)
Article
Engineering, Industrial
Yuling Li, Frank W. Guldenmund, Olga N. Aneziris
Editorial Material
Engineering, Industrial
Tom Kontogiannis, M. C. Leva, Olga Aneziris
Article
Engineering, Industrial
O. N. Aneziris, Z. Nivolianitou, M. Konstandinidou, G. Mavridis, E. Plot
Article
Chemistry, Physical
Karolien van Nunen, Paul Swuste, Genserik Reniers, Nicola Paltrinieri, Olga Aneziris, Koen Ponnet
Article
Engineering, Chemical
N. Defteraios, C. Kyranoudis, Z. Nivolianitou, O. Aneziris
JOURNAL OF LOSS PREVENTION IN THE PROCESS INDUSTRIES
(2020)
Review
Engineering, Industrial
Olga Aneziris, Ioanna Koromila, Zoe Nivolianitou
Article
Engineering, Industrial
Olga Aneziris, Marko Gerbec, Ioanna Koromila, Zoe Nivolianitou, Francesco Pilo, Ernesto Salzano
Summary: The SUPER-LNG project has achieved significant milestones by developing guidelines and training programs to enhance safety reporting and risk assessment for small-scale LNG facilities, while also increasing stakeholders' safety and knowledge levels on the LNG fuel chain.
Article
Engineering, Industrial
Ioanna Koromila, Olga Aneziris, Zoe Nivolianitou, Angeliki Deligianni, Evangelos Bellos
Summary: This study analyzed relevant stakeholders in the safety management of LNG in Greek ports and created three stakeholder networks using social network analysis. Statistics and metrics of the networks were calculated using open-source software to identify the most important stakeholders in LNG safety management.
Article
Engineering, Industrial
Hao Sun, Haiqing Wang, Ming Yang, Genserik Reniers
Summary: To maintain continuous production, chemical plant operators may choose to ignore or handle faults online rather than shutting down process systems. However, the interaction and interdependence between components in a digitalized process system are significant, and faults can propagate to downstream nodes, potentially leading to risk accumulation and major accidents. This study proposes a dynamic risk assessment method that integrates the system-theoretic accident model and process approach (STAMP) with the cascading failure propagation model (CFPM) to model the risk accumulation process. The proposed method is applied to a Chevron refinery crude unit and demonstrates its effectiveness in quantifying the process of risk accumulation and providing real-time dynamic risk profiles for decision-making.
Article
Engineering, Industrial
M. Rempel
Summary: This article examines a major maritime disaster scenario and explores the evacuation process in such a situation. The study finds that there are various factors that affect the number of lives saved, including the uncertainty of individuals' medical condition, the arrival time of maritime and air assets, and the decision policies used. The authors formulate the multi-domain operation as a sequential decision problem using a modeling framework and provide decision support through a hypothetical case study.
Review
Engineering, Industrial
D. Scorgie, Z. Feng, D. Paes, F. Parisi, T. W. Yiu, R. Lovreglio
Summary: This study investigates the application and effectiveness of VR safety training solutions in various industries such as construction, fire, aviation, and mining. The findings suggest a need for more studies that adopt theories and measure long-term retention. Two meta-analyses demonstrate that VR safety training outperforms traditional training in terms of knowledge acquisition and retention.
Article
Engineering, Industrial
Shital Thekdi, Terje Aven
Summary: This paper examines biases in risk studies and investigates how to identify and address them to ensure high-quality risk analysis. By considering biases related to systematic error, event inclusion, models, and cognitive factors, the paper explores their influence on risk characterization. The insights gained from this exploration can be valuable to risk analysts, policymakers, and other stakeholders involved in risk study applications.
Article
Engineering, Industrial
Maryam Lari
Summary: Occupational health and safety (OHS) are crucial for employee well-being and productivity. This study examines the impact of OHS practices on employee productivity in a UAE Fire and Security company, finding that OHS interventions can enhance workplace ambiance and significantly boost employee productivity.
Review
Engineering, Industrial
Elleke Ketelaars, Cyrille Gaudin, Simon Flandin, Germain Poizat
Summary: This systematic literature review examines the literature on resilience training (RT), specifically focusing on the effectiveness of RT interventions in preparing professionals to effectively respond to critical situations. The review identifies five types of RT and suggests the need for conceptual advancements, vocational education and training perspectives, and a cross-disciplinary approach in future research to enhance resilience in safety-related domains.
Article
Engineering, Industrial
Meng Shi, Zhichao Zhang, Wenke Zhang, Yi Ma, Hanbo Li, Eric Wai Ming Lee
Summary: This study investigates pedestrian behaviours and evacuation processes in both fire and non-fire conditions using Minecraft. The results demonstrate the potential of Minecraft for realistically simulating evacuation processes, as the behaviours and flow patterns of pedestrians in virtual experiments fit well with real-life experiments. The study also shows that pedestrians exhibit fire avoidance behaviours and orderly queuing during a fire emergency, resulting in faster evacuation.
Article
Engineering, Industrial
Andrea Bikfalvi, Esperanza Villar Hoz, Gerusa Gimenez Leal, Monica Gonzalez-Carrasco, Nuria Mancebo
Summary: This paper proposes a solution for integrating occupational safety and health (OSH) into education, combining theoretical foundations and empirical evidence. The findings include analysis of teachers as stakeholders, barriers and facilitators of OSH integration, and the development of an ICT tool for interaction and sharing in this field. The main contribution lies in envisioning, orchestrating, and validating a solution to integrate OSH into schools and ultimately contribute to sustainable development goals.
Article
Engineering, Industrial
David Rehak, Alena Splichalova, Martin Hromada, Neil Walker, Heidi Janeckova, Josef Ristvej
Summary: This article discusses the adoption of a new directive on the resilience of critical entities and emphasizes the importance of assessing their level of resilience in relation to current security threats. The authors have developed a tool, known as the CERFI Tool, which uses a probabilistic algorithm to predict the failure point of critical entity resilience based on the relationship between threat intensity and protection. The tool is important for increasing the safety of technically oriented infrastructures, particularly in the energy and transport sectors.
Review
Engineering, Industrial
Leonardo Leoni, Ahmad Bahootoroody, Mohammad Mahdi Abaei, Alessandra Cantini, Farshad Bahootoroody, Filippo De Carlo
Summary: This paper presents a systematic bibliometric analysis (SBA) on the research of machine learning and deep learning in the field of safety. The main research areas, application fields, relevant authors and studies, and temporal evolution are investigated. It is found that rotating equipment, structural health monitoring, batteries, aeroengines, and turbines are popular fields, and there is an increase in popularity of deep learning and new approaches such as deep reinforcement learning.
Article
Engineering, Industrial
Tom Becker, Peter Ayton
Summary: By analyzing global civil aviation data, we found that there is a significant increase in the number of accidents and safety critical incidents, as well as the fatalities, when the Pilot-in-Command acts as the Pilot Flying instead of the Pilot Monitoring. Most of these events occurred in technically airworthy aircraft without any emergencies, and the flight crew assessed them as preventable. These findings align with the crew assignment effect, suggesting that role-dependent status hierarchy and cognitive overload contribute to ineffective flight crew teamwork. The measures implemented to enhance flight crew teamwork, such as Crew Resource Management training, have not been successful in preventing these issues.
Article
Engineering, Industrial
Ben Hutchinson, Sidney Dekker, Andrew Rae
Summary: This study found that health and safety audits often fail to identify critical deficiencies, with corrective actions mainly focusing on superficial fixes rather than addressing significant operational risks.
Review
Engineering, Industrial
Sina Rasouli, Yaghoub Alipouri, Shahin Chamanzad
Summary: Construction projects are risky environments, but the development of Personal Protective Equipment (PPE) and comprehensive safety management can effectively control the number of accidents.
Article
Engineering, Industrial
Laura Mills, Verity Truelove
Summary: This study investigated the use of police location communities (PLCs) for obtaining information about roadside drug testing (RDT) among drivers, and found that drivers who used PLCs were more concerned about being caught for drug driving, had a better understanding of the related penalties and procedures, and knew others who also used PLCs to avoid detection for drug driving. Furthermore, the study found that the use of PLCs was associated with choosing back roads for driving, which may reduce the risk of detection for drug driving.
Review
Engineering, Industrial
Chao Wu, Xi Huang, Bing Wang
Summary: After decades of development, the safety discipline in China has made remarkable progress. The project led by the Safety & Security Theory Innovation and Promotion Center of Central South University has filled the gaps in safety science education by creating textbooks and courses for postgraduate students. These achievements have played an important role in the development of safety science and can serve as a reference for basic research and talent training in safety science globally.