Research Project: Developing a Model of Teamwork in Air Traffic Control

Background

Air traffic in world is increasing at a rapid rate, and thus it has been desired to increase the capacity of each en route. Because the en route capacity is mainly determined by workload of air traffic controllers (ATCOs), many researchers have proposed a variety of cognitive models and different methods to assess ATCOs’ workload in en route air traffic control (ATC); past studies, however, have often focused only on tactical controller in spite of the fact that en route ATC is a team coordination task conducted by tactical controller (TC) and planning controller (PC) who assists the TC. Understanding of team cooperation between TCs and PCs is essential for understanding cognitive processes of ATCOs and measuring workload because, for example, assistance of the PC can reduce the TC’s workload and improve their performance.

Methodology

This study focuses on the team cooperation of ATCOs in en route ATC and has two purposes; one is to propose a classification method of interaction of ATCOs (tactical controller and planning controller) in en route ATC. The method consists of two categories: the category of intentions and that of contents. The category of intentions that represents why a member starts to communicate is derived from a team cognition model based on mutual belief, and the category of contents that represents what a member talks about is derived from a simple hierarchical task analysis. Using the both categories, an interaction classification matrix is developed. The matrix is expected to measure the effect of introducing a new ATC system on team cooperation between TC and PC. The other purpose is to develop a cognitive model of team cooperation in en route ATC. This research has applied the developed matrix to interaction data in Tokyo ACC and described interaction processes between the TC and the PC in order to collect qualitative and quantitative findings about team cooperation in en-route ATC. A cognitive model of team cooperation in en route ATC is being developed using the collected findings in the analysis and those of the past studies. The most notable point of the model will be asymmetrical relationships between TC and PC (e.g. monitoring about TC’s cognition by PC).

Sponsorship

This research was sponsored by the Japan Society for the Promotion of Science.

Publications

Nonose, K. Majumdar, A., Inoue, S., Aoyama, H., Kanno, T., and K. Furuta (2012) A cognition model of teamwork in en route air traffic control, Proceedings of the Applied Human Factors and Ergonomics International 2012 Conference. San Francisco, USA, July 21-25 2012.

Research Project: Fatigue Monitoring and Analysis in Airline Operations

Background

Low cost airlines in Europe have become a major player in the aviation sector. Such airlines have a considerably different manner of operations than long-haul airlines, in particular with pilots flying early morning duties with four routes a day. This in turn has caused considerable concerns regarding the safety of such carriers, in particular the workload and fatigue of the pilots. One of the aims of the major low cost carrier's, easyJet, Human Factors Monitoring Programme (HFMP) is to link instances of fatigue-related risk precursors in crew schedules to crew performance. Therefore, it analyses the effects on recovery sleep over a longer time period of crew schedules in order to overcome data limitations that are apparent in previous domain-dependent studies.

Methodology

The objective of this research program is to minimise the number and complexity of these measurements by showing reliable associations among them so as to identify the simplest reliable measurement system for monitoring fatigue performance. This study assesses the statistical relationships relating to crew performance measures across the flexible roster variation. The members of The LRET TRMC have already completed two studies. One is based upon a sample of 22 pilots. The other is based on cabin crew. A further major study with pilots was conducted in the summer of 2011 and is currently being analysed.

Collaboration

This research is conducted in collaboration with NASA and easyjet.

Research Project: A Human Reliability Analysis (HRA) Technique to improve Railway Safety

Background

The railway system constitutes an important means of transport around the world. Each day it transports millions of passengers and millions of dollars worth of goods from one end to another. The safety of railway operations depends on several factors including rail traffic rules, infrastructure reliability, organisations safety culture and human factors. With respect to human factors it is notable that over the years a large number of railway incidents and accidents have occurred due to human performance, hence it is a significant contributor to railway occurrences.

On account of that, the reliability and safety level of the rail network is dependent on the performance of the human operators, which can be either enhanced or degraded by a number of factors such as training, working conditions, organisational factors or available time to perform a task, broadly known as Performance Shaping Factors (PSFs). The literature shows that it is the train drivers, signallers and controllers who mostly affect the network in terms of safety.

Several studies have been conducted in the field of HFs and human performance in the railway domain. However, most of these are based on previous studies in the field of Human Reliability Analysis (HRA) from other domains. Hence, they are not well suited to the rail industry and can be difficult to apply reliably to railway specific operations.

Methodology and Collaborations

In light of the current limitations, this study proposes a new approach referred to as the Human Performance Railway Operational Index (HuPeROI). The approach aims not only to estimate the human error probability for railway operations but also to propose mitigation strategies to minimise phenomena such as operators’ degraded performance. HuPeROI is based on a PSFs taxonomy designed for the rail industry. This taxonomy, referred to as the Railway Performance Shaping Factors (R-PSFs), is developed based on an extensive literature review of the field of HFs. In addition, data from several European rail organisations have been used such as: the Swiss Federal Railways; the Norwegian Railways; data from U.K. Network Rail; data from ERADIS database as well as data from the U.S.A, Canadian and Australian Transport Safety Boards. Subsequently, subject matter experts (SMEs) validate and assess the taxonomy, whilst they also weight and rank the factors of R-PSFs taxonomy, which afterwards are used to develop the HuPeROI.

Publications

1. Kyriakidis, M. A., Hirsch, R. and A. Majumdar (2012) Metro Railway Safety: an analysis of accident precursors, Safety Science, 50, pp. 1535-1548.
2. Kyriakidis, M., Majumdar, A., Grote, G., and W.Y. Ochieng (2012) The development and assessment of a performance shaping factors taxonomy for railway operations, Transportation Research Record: Journal of the Transportation Research Board, Washington D.C., USA, (accepted).
3. Kyriakidis, M., Majumdar, A., Washington, Y.O. (2012) A Human Performance Operational Railway Index to estimate operators’ error probability, Proceedings of the Applied Human Factors and Ergonomics International 2012 Conference. San Francisco, USA, July 21-25 2012.
4. Kyriakidis, M., Majumdar, A., Grote, G., Washington, Y.O. (2012) The development and assessment of a performance shaping factors taxonomy for railway operations, Proceedings of the Transportation Research Board 91st Annual Meeting. Washington D.C., USA, Jan 22-26 2012.
5. Kyriakidis, M. (2011) Human Reliability Analysis, In Kröger, W. & Zio, E. (eds.) Vulnerable Systems. Springer, pp. 157-187.