190 research outputs found

    Sureline

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    Seeing the woods for the trees: the problem of information inefficiency and information overload on operator performance

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    One of the recurring questions in designing dynamic control environments is whether providing more information leads to better operational decisions. The idea of having every piece of information and increasing situation awareness is so tempting (and in safety critical domains often mandatory) that has become an obstacle for designers and operators. This research examined this challenge within a railway control setting. A laboratory study was conducted to investigate the presentation of different levels of information (taken from data processing framework, Dadashi et al., 2014) and the association with, and potential prediction of, the performance of a human operator when completing a cognitively demanding problem solving scenario within railways. Results indicated that presenting users with information corresponding to their cognitive task (and no more) improves the performance of their problem solving/alarm handling. Knowing the key features of interest to various agents (machine or human) and using the data processing framework to guide the optimal level of information required by each of these agents could potentially lead to safer and more usable designs

    Modelling decision-making within rail maintenance control rooms

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    This paper presents a cognitive task analysis to derive models of decision-making for rail maintenance processes. Maintenance processes are vital for safe and continuous availability of rail assets and services. These processes are increasingly embracing the ‘Intelligent Infrastructure’ paradigm, which uses automated analysis to predict asset state and potential failure. Understanding the cognitive processes of maintenance operators is critical to underpin design and acceptance of Intelligent Infrastructure. A combination of methods, including observation, interview and an adaptation of critical decision method, was employed to elicit the decision-making strategies of operators in three different types of maintenance control centre, with three configurations of pre-existing technology. The output is a model of decision-making, based on Rasmussen’s decision ladder, that reflects the varying role of automation depending on technology configurations. The analysis also identifies which types of fault were most challenging for operators and identifies the strategies used by operators to manage the concurrent challenges of information deficiencies (both underload and overload). Implications for design are discussed

    Impact of automation: measurement of performance, workload and behaviour in a complex control environment

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    This paper describes an experiment that was undertaken to compare three levels of automation in rail signalling; a high level in which an automated agent set routes for trains using timetable information, a medium level in which trains were routed along pre-defined paths, and a low level where the operator (signaller) was responsible for the movement of all trains. These levels are described in terms of a Rail Automation Model based on previous automation theory (Parasuraman et al., 2000). Performance, subjective workload, and signaller activity were measured for each level of automation running under both normal operating conditions and abnormal, or disrupted, conditions. The results indicate that perceived workload, during both normal and disrupted phases of the experiment, decreased as the level of automation increased and performance was most consistent (i.e. showed the least variation between participants) with the highest level of automation. The results give a strong case in favour of automation, particularly in terms of demonstrating the potential for automation to reduce workload, but also suggest much benefit can achieved from a mid-level of automation potentially at a lower cost and complexity

    Seeing the woods for the trees: the problem of information inefficiency and information overload on operator performance

    Get PDF
    One of the recurring questions in designing dynamic control environments is whether providing more information leads to better operational decisions. The idea of having every piece of information and increasing situation awareness is so tempting (and in safety critical domains often mandatory) that has become an obstacle for designers and operators. This research examined this challenge within a railway control setting. A laboratory study was conducted to investigate the presentation of different levels of information (taken from data processing framework, Dadashi et al., 2014) and the association with, and potential prediction of, the performance of a human operator when completing a cognitively demanding problem solving scenario within railways. Results indicated that presenting users with information corresponding to their cognitive task (and no more) improves the performance of their problem solving/alarm handling. Knowing the key features of interest to various agents (machine or human) and using the data processing framework to guide the optimal level of information required by each of these agents could potentially lead to safer and more usable designs

    Using mobile phones in pub talk

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    We present the findings from a study of how people interleave mobile phone use with conversation in pubs. Our findings, informed by ethnomethodology and conversation analysis, unpack the interactional methods through which groups of people in pubs occasioned, sustained, and disengaged from mobile device use during conversation with friends. Fundamentally, the work that is done consists of various methods of accounting for mobile device use, and displaying involvement in social interaction while the device is used. We highlight multiple examples of the nuanced ways in which interleaving is problematic in interaction, and relate our findings to the CSCW and HCI literature on collocated interaction. We conclude by considering avenues for future research, and discuss how we may support or disrupt interleaving practices through design to overcome the highlighted interactional troubles

    The experience of couples being given an oxygen concentrator to use at home: A longitudinal interpretative phenomenological analysis

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    This longitudinal study explores the lived experience of four couples where one person from each couple is prescribed an oxygen concentrator to use at home. Transcripts were analysed using interpretative phenomenological analysis. The findings reported here focus on two super-ordinate themes: ‘the journey of acceptance’ and ‘negotiating changing relationships’. Participants described a gradual process of accepting the device into their lives, the impact on couple’s relationships and the role that expectations have in mediating that process. These themes suggest that patient education that considers the psychological and social issues may prove useful in facilitating the acceptance process

    A study of effective evaluation models and practices for technology supported physical learning spaces (JELS)

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    The aim of the JELS project was to identify and review the tools, methods and frameworks used to evaluate technology supported or enhanced physical learning spaces. A key objective was to develop the sector knowledgebase on innovation and emerging practice in the evaluation of learning spaces, identifying innovative methods and approaches beyond traditional post-occupancy evaluations and surveys that have dominated this area to date. The intention was that the frameworks and guidelines discovered or developed from this study could inform all stages of the process of implementing a technology supported physical learning space. The study was primarily targeted at the UK HE sector and the FE sector where appropriate, and ran from September 2008 to March 2009

    Development of a technique for predicting the human response to an emergency situation

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    This paper presents development work on a new approach for predicting the human response to an emergency situation. The study builds upon an initial investigation in which 20 participants were asked to predict what actions they would take in the event of a domestic fire [1]. The development work involved a retest with an additional 20 participants to investigate the reliability of the approach. Furthermore, the analysis procedure was improved such that the results represented more accurately those which could be obtained from practical application of the approach. As found in the initial investigation, the frequencies and sequences of the reported acts had significant relationships with a study of behavior in real fires [2] (Spearman’s rho: 0.323, N=55, p<0.05) and (Spearman’s rho: 0.340, N=37, p<0.05), respectively. Further development work is required, but the results indicate that the approach may have use for predicting human behavior in emergencies
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