Hostname: page-component-cd9895bd7-gbm5v Total loading time: 0 Render date: 2024-12-18T07:47:18.611Z Has data issue: false hasContentIssue false
  • English
  • Français

Causal Factors and Symptoms of Task-Related Human Fatigue in Vessel Traffic Service: A Task-Driven Approach

Published online by Cambridge University Press:  23 June 2020

Fan Li Open the ORCID record for Fan Li [Opens in a new window] ,
Chun-Hsien Chen ,
Gangyan Xu ,
Danni Chang Open the ORCID record for Danni Chang [Opens in a new window]  and
Li Pheng Khoo
Fan Li
Affiliation:
(School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore)
Chun-Hsien Chen
Affiliation:
(School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore)
Gangyan Xu
Affiliation:
(Center of Urban Emergency Management and Traffic Safety, School of Architecture, Harbin Institute of Technology, Shenzhen, China) (Intelligent Transportation Lab, Shenzhen Key Laboratory of Urban Planning and Decision Making, Harbin Institute of Technology, Shenzhen, China)
Danni Chang*
Affiliation:
(School of Design, Shanghai Jiao Tong University, Shanghai, China)
Li Pheng Khoo
Affiliation:
(School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore)
*
(E-mail: [email protected])
Get access Rights & Permissions [Opens in a new window]

Abstract

Human fatigue is a major risk factor in transportation that contributes, directly or indirectly, to a large number of traffic accidents. Though many studies have investigated fatigue-inducing factors in transportation to manage human fatigue more efficiently, there are limited studies related to vessel traffic service (VTS). To fill this gap, this work aims to determine the key causal factors and symptoms of human fatigue with a focus on VTS operations. Achieving this aim is hindered by the problems of no standard definition of task-related fatigue and limited data sources. To solve these problems, this paper proposes a novel definition of task-related human fatigue, a task-driven approach for identifying causal factors and a causal network-based approach for selecting key causal factors. Twelve key causal factors of human fatigue in VTS were identified and analysed. In addition, it was found that VTS operators suffered from multidimensional fatigue, especially physical fatigue. The results provide a foundation and future directions for designing interventions to manage human fatigue.

Keywords

Human FatigueTask-DrivenCausal FactorsHuman Fatigue Causal NetworkVessel Traffic Service
Type
Research Article
Information
The Journal of Navigation , Volume 73 , Issue 6 , November 2020 , pp. 1340 - 1357
Check for updates
Copyright
Copyright © The Royal Institute of Navigation 2020

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Ahsberg, E., Gamberale, F. and Gustafsson, K. (2000). Perceived fatigue after mental work: an experimental evaluation of a fatigue inventory. Ergonomics, 43, 252–268.10.1080/001401300184594CrossRefGoogle ScholarPubMed
Akhtar, M. J. and Utne, I. B. (2014). Human fatigue's effect on the risk of maritime groundings – A Bayesian network modeling approach. Safety Science, 62, 427–440.CrossRefGoogle Scholar
Alonso, F., Esteban, C., Useche, S. A. and López De Cózar, E. (2016). Prevalence of physical and mental fatigue symptoms on Spanish drivers and its incidence on driving safety. Advances in Psychology Neuroscience, 1, 10–18.Google Scholar
Bal, E., Arslan, O. and Tavacioglu, L. (2015). Prioritization of the causal factors of fatigue in seafarers and measurement of fatigue with the application of the lactate test. Safety Science, 72, 46–54.10.1016/j.ssci.2014.08.003CrossRefGoogle Scholar
Bye, R. J. and Aalberg, A. L. (2018). Maritime navigation accidents and risk indicators: An exploratory statistical analysis using AIS data and accident reports. Reliability Engineering & System Safety, 176, 174–186.CrossRefGoogle Scholar
Chang, Y.-H., Yang, H.-H. and Hsu, W.-J. (2019). Effects of work shifts on fatigue levels of air traffic controllers. Journal of Air Transport Management, 76, 1–9.10.1016/j.jairtraman.2019.01.013CrossRefGoogle Scholar
Charbonnier, S., Roy, R. N., Bonnet, S. and Campagne, A. (2016). EEG index for control operators' mental fatigue monitoring using interactions between brain regions. Expert Systems with Applications, 52, 91–98.10.1016/j.eswa.2016.01.013CrossRefGoogle Scholar
Chen, S.-T., Wall, A., Davies, P., Yang, Z., Wang, J. and Chou, Y.-H. (2013). A human and organisational factors (HOFs) analysis method for marine casualties using HFACS-Maritime Accidents (HFACS-MA). Safety Science, 60, 105–114.CrossRefGoogle Scholar
Chen, M.-L., Lu, S.-Y. and Mao, I.-F. (2019). Subjective symptoms and physiological measures of fatigue in air traffic controllers. International Journal of Industrial Ergonomics, 70, 1–8.10.1016/j.ergon.2018.12.004CrossRefGoogle Scholar
De Ambroggi, M. and Trucco, P. (2011). Modelling and assessment of dependent performance shaping factors through analytic network process. Reliability Engineering & System Safety, 96, 849–860.CrossRefGoogle Scholar
Desmond, P. A. and Hancock, P. A. (2001). Active and passive fatigue states. In: Hancock, P. A. and Desmond, P. A. (eds.), Human factors in transportation. Stress, workload, and fatigue, Lawrence Erlbaum Associates Publishers, 455–465.Google Scholar
Dodge, R. E. (1982). Circadian rhythms and fatigue: a discrimination of their effects on performance. Aviation, Space, and Environmental Medicine, 53, 1131–1136.Google ScholarPubMed
Edwards, M. (1981). The design of an accident investigation procedure. Applied Ergonomics, 12, 111–115.10.1016/0003-6870(81)90178-2CrossRefGoogle ScholarPubMed
Freeman, L. C. (1977). A set of measures of centrality based on betweenness. Sociometry, 35–41.10.2307/3033543CrossRefGoogle Scholar
Gander, P. (2001). Fatigue management in air traffic control: the New Zealand approach. Transportation Research Part F: Traffic Psychology and Behaviour, 4, 49–62.10.1016/S1369-8478(01)00013-4CrossRefGoogle Scholar
Herlambang, M. B., Taatgen, N. A. and Cnossen, F. (2019). The role of motivation as a factor in mental fatigue. Human Factors, 61, 1171–1185.CrossRefGoogle ScholarPubMed
Hirshkowitz, M. (2013). Fatigue, sleepiness, and safety: definitions, assessment, methodology. Sleep Medicine Clinics, 8(2), 183–189.10.1016/j.jsmc.2013.04.001CrossRefGoogle Scholar
Hockey, R. (2013). The Psychology of Fatigue: Work, Effort and Control. Cambridge University Press.CrossRefGoogle Scholar
Hollnagel, E. (1998). Cognitive Reliability and Error Analysis Method (CREAM). Elsevier Science.Google Scholar
Hughes, T. (1998). Vessel traffic services (VTS): Are we ready for the new millenium?. The Journal of Navigation, 51, 404–420.10.1017/S0373463398007954CrossRefGoogle Scholar
Hughes, C. T. (2009). When Is a VTS not a VTS? The Journal of Navigation, 62, 439–442.CrossRefGoogle Scholar
IALA (2009). Recommendation (V-103) Standards for Training and Certification of VTS Personnel. Saint Germain en Laye, France: IALA.Google Scholar
Jepsen, J. R., Zhao, Z., Pekcan, C., Barnett, M. and Van Leeuwen, W. M. (2017). Risk factors for fatigue in shipping, the consequences for seafarers' health and options for preventive intervention. In Maritime Psychology: Springer, Cham, pp. 127–150.CrossRefGoogle Scholar
Ji, Q., Lan, P. and Looney, C. (2006). A probabilistic framework for modeling and real-time monitioring human fatigue. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, Vol. 36, pp. 862–875.Google Scholar
Job, R. and Dalziel, J. (2001). Defining fatigue as a condition of the organism and distinguishing it from habituation, adaptation, and boredom. In: Hancock, P. A. and Desmond, P. A. (eds.) Human factors in transportation. Stress, workload, and fatigue, Lawrence Erlbaum Associates Publishers, 466–475.Google Scholar
Li, F., Chen, C.-H. and Khoo, L. P. (2016). Information requirements for vessel traffic service operations. World Academy of Science, Engineering and Technology, International Journal of Computer, Electrical, Automation, Control and Information Engineering, 10, 881–885.Google Scholar
Li, F., Lee, C.-H., Chen, C.-H. and Khoo, L. P. (2019). Hybrid data-driven vigilance model in traffic control center using eye-tracking data and context data. Advanced Engineering Informatics, 42, 100940.10.1016/j.aei.2019.100940CrossRefGoogle Scholar
Liu, P., Lyu, X., Qiu, Y., He, J., Tong, J., Zhao, J. and Li, Z. (2017). Identifying key performance shaping factors in digital main control rooms of nuclear power plants: A risk-based approach. Reliability Engineering & System Safety, 167, 264–275.CrossRefGoogle Scholar
Liu, Y., Trapsilawati, F., Lan, Z., Sourina, O., Johan, H., Li, F., Chen, C.-H. and Mueller-Wittig, W. (2019). Human Factors Evaluation of ATC Operational Procedures in Relation to Use of 3D Display. International Conference on Applied Human Factors and Ergonomics, Kyoto, Japan: Springer, Cham, pp. 715–726.Google Scholar
Masoudian, M. and Razavi, H. (2018). An investigation of the required vigilance for different occupations. Safety Science, 119, 353–359.CrossRefGoogle Scholar
May, J. F. and Baldwin, C. L. (2009). Driver fatigue: The importance of identifying causal factors of fatigue when considering detection and countermeasure technologies. Transportation Research Part F: Traffic Psychology and Behaviour, 12, 218–224.CrossRefGoogle Scholar
Michalaki, P., Quddus, M. A., Pitfield, D. and Huetson, A. (2015). Exploring the factors affecting motorway accident severity in England using the generalised ordered logistic regression model. Journal of Safety Research, 55, 89–97.Google ScholarPubMed
Miles, M. and Huberman, A. M. (1984). Qualitative Data Analysis: A Sourcebook of New Methods. Beverly Hills, CA: Sage.Google Scholar
Montgomery, L. D., Montgomery, R. W. and Guisado, R. (1995). Rheoencephalographic and electroencephalographic measures of cognitive workload: analytical procedures. Biological Psychology, 40, 143–159.CrossRefGoogle ScholarPubMed
Niemeijer, D. and de Groot, R. S. (2008). Framing environmental indicators: moving from causal chains to causal networks. Environment, Development and Sustainability, 10, 89–106.CrossRefGoogle Scholar
Paterson, J. L., Sofianopoulos, S. and Williams, B. (2014). What paramedics think about when they think about fatigue: Contributing factors. Emergency Medicine Australasia, 26, 139–144.10.1111/1742-6723.12216CrossRefGoogle ScholarPubMed
Phillips, R. O. (2015). A review of definitions of fatigue – and a step towards a whole definition. Transportation Research Part F: Traffic Psychology and Behavior, 29, 48–56.Google Scholar
Praetorius, G. (2012). Safety within the Vessel Traffic Service (VTS) Domain. Understanding the role of the VTS for safety within maritime traffic management. Licentiate thesis, Department of Shipping and Marine Technology. Gothenburg, Chalmers University of Technology.Google Scholar
Praetorius, G., Van Westrenen, F., Mitchell, D. L. and Hollnagel, E. (2012). Learning Lessons in Resilient Traffic Management: A Cross-Domain Study of Vessel Traffic Service and Air Traffic Control. HFES Europe Chapter Conference Toulouse 2012, 2012. HFES Europe Chapter, pp. 277–287.Google Scholar
Reason, J. (1990). The contribution of latent human failures to the breakdown of complex systems. Philosophical Transactions of the Royal Society of London. B, Biological Sciences, 327, 475–484.Google ScholarPubMed
Renata, V., Li, F., Lee, C.-H. and Chen, C.-H. (2018). Investigation on the Correlation Between Eye Movement and Reaction Time under Mental Fatigue Influence. In Proceedings of the 17th Cyberworlds International Conference (CW 2018), October 3–5 2018, Singapore. IEEE, pp. 207–213.10.1109/CW.2018.00046CrossRefGoogle Scholar
Sallinen, M. and Hublin, C. (2015). Fatigue-inducing factors in transportation operators. Reviews of Human Factors and Ergonomics, 10, 138–173.CrossRefGoogle Scholar
Shen, J., Barbera, J., and Shapiro, C. M. (2006). Distinguishing sleepiness and fatigue: focus on definition and measurement. Sleep medicine reviews, 10, 63–76.10.1016/j.smrv.2005.05.004CrossRefGoogle Scholar
Stricker, G. (2010). American Psychological Association Code of Ethics. The Corsini Encyclopedia of Psychology, 4, 1–2.Google Scholar
Trejo, L. J., Kubitz, K., Rosipal, R., Kochavi, R. L. and Montgomery, L. D. (2015). EEG-based estimation and classification of mental fatigue. Psychology, 6, 572–589.CrossRefGoogle Scholar
Van Cutsem, J., Marcora, S., De Pauw, K., Bailey, S., Meeusen, R. and Roelands, B. (2017). The effects of mental fatigue on physical performance: a systematic review. Sports Medicine, 47, 1569–1588.CrossRefGoogle ScholarPubMed
Wolf, L. A., Perhats, C., Delao, A. and Martinovich, Z. (2017). The effect of reported sleep, perceived fatigue, and sleepiness on cognitive performance in a sample of emergency nurses. Journal of Nursing Administration, 47, 41–49.CrossRefGoogle Scholar
Xu, G., Li, F., Chen, C.-H., Lee, C.-H. and Lee, Y.-C. (2015). Toward resilient vessel traffic service: A Sociotechnical Perspective. Proceedings of the 24th ISPE Inc. International Conference on Transdisciplinary Engineering: A Paradigm Shift, Singapore, July 10–14, pp. 829–836.Google Scholar
Zuraida, R. and Iridiastadi, H. (2015). Evaluation of subjective fatigue tool-a study addressing restaurant employees in Indonesia. In 2015 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). Singapore, December 6–9, IEEE. pp. 1083–1086.CrossRefGoogle Scholar