Nastaran Dadashi

Practical use of work analysis to support rail electrical control rooms: A case of alarm handling

Renewals and especially enhancements of rail signalling and control systems are increasingly including a strong programme of human factors integration. One contribution to the human factors work that is required is work analysis – the understanding of what tasks and functions exist in current work systems, the artefacts (controls and displays used) and the strategies employed by skilled operators. One increasingly common approach to such work systems analysis is cognitive work analysis (CWA), used to develop understanding of a work domain and tasks in a structured fashion and as a basis for new design recommendations. The purpose of this paper is to explain, for an engineering and systems developer audience, the basis for and use of CWA. This is done in the context of rail electrical control rooms and especially the use made of various information display elements including alarms.

A framework to support human factors of automation in railway intelligent infrastructure

Technological and organisational advances have increased the potential for remote access and proactive monitoring of the infrastructure in various domains and sectors – water and sewage, oil and gas and transport. Intelligent Infrastructure (II) is an architecture that potentially enables the generation of timely and relevant information about the state of any type of infrastructure asset, providing a basis for reliable decision-making. This paper reports an exploratory study to understand the concepts and human factors associated with II in the railway, largely drawing from structured interviews with key industry decision-makers and attachment to pilot projects. Outputs from the study include a data-processing framework defining the key human factors at different levels of the data structure within a railway II system and a system-level representation. The framework and other study findings will form a basis for human factors contributions to systems design elements such as information interfaces and role specifications. Practitioner Summary: The framework reported in this paper can become the basis for human factors guidance of engineers, developers and business analysts in developing appropriate levels of information display, automation and decision aid into rail II. Guidance will be aimed at the different functions and activities within multi-layered, multi-agent control.

The characteristics of railway service disruption: implications for disruption management

Abstract Rail disruption management is central to operational continuity and customer satisfaction. Disruption is not a unitary phenomenon – it varies by time, cause, location and complexity of coordination. Effective, user-centred technology for rail disruption must reflect this variety. A repertory grid study was conducted to elicit disruption characteristics. Construct elicitation with a group of experts (n = 7) captured 26 characteristics relevant to rail disruption. A larger group of operational staff (n = 28) rated 10 types of rail incident against the 26 characteristics. The results revealed distinctions such as business impact and public perception, and the importance of management of the disruption over initial detection. There were clear differences between those events that stop the traffic, as opposed to those that only slow the traffic. The results also demonstrate the utility of repertory grid for capturing the characteristics of complex work domains. Practitioner Summary: The aim of the paper is to understand how variety in rail disruption influences socio-technical design. It uses repertory grid to identify and prioritise 26 constructs, and group 10 disruption types, identifying critical factors such as whether an incident stops or merely slows the service, and business reputation.

A framework of data processing for decision making in railway intelligent infrastructure

Intelligent infrastructure is an architecture that enables generation of immediate, accurate and relevant information about the state of any type of infrastructural asset and converts this information to timely and reliable decision aids. The study presented in this paper identifies the scope of railway intelligent infrastructure system via a mixed contextual and sequential approach. The output from this study is a framework that identifies and explores the data processes required for decision making within a railway intelligent infrastructure system. Findings will assist designers to present the correct level of detail for various stages identified for intelligent infrastructure

Disruption management processes during emergencies on the railways

The following study presents an analysis of incident logs, recorded during major rail incidents (incurring more than 1,000 minutes total delay) to understand regular patterns in management and resolution across different incident types and across multiple roles. The analysis found that much effort goes into coordination of multiple actors and diagnosing both the cause and scale of the disrupting factor, as would be expected. Rather than events taking place merely in parallel, they are closely intertwined, with activities in one area (e.g., repairs to reopen track) being constrained by other activities (e.g., coordinating and mobilising appropriate people, arranging track access within a rescheduled service). These results question existing linear models of disruption management, both at an individual and organisational level, and have implications for decision-support for emergency management.

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

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 is increasingly tempting (and in safety critical domains often mandatory) but has become a potential obstacle for designers and operators. The present research study examined this challenge of appropriate information design and usability 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. in Ergonomics 57(3):387–402, 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 only with information corresponding to their cognitive task, and in the absence of other, non task-relevant information, 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.

Automatic Components of Integrated CCTV Surveillance Systems: Functionality, Accuracy and Confidence

Recent societal events and advances in computer vision technology have lead to the development of a variety of automatic surveillance systems. Despite their arguable success in the laboratory, fully automatic methods remain unsuitable for use in real life situations due to the complex nature of the context in which they must operate. Current techniques may, however, be immediately valuable if deployed as components of integrated human-automatic CCTV surveillance systems. It is therefore important to understand the potential of current automatic methods and provide design recommendations for semi-automatic systems, so that work to date can be exploited in full. An experiment was conducted to investigate the importance of the functionality and level of accuracy of, and feedback provided by, the automatic component of an integrated, semi-automatic CCTV surveillance system. The operators’ workload and spare attentional capacity was measured to investigate the effect of each of these factors. Results showed significant reduction in workload when reliable confidence information is fed back. Increases in accuracy and variation in functionality failed to produce evidence of change in workload.

Alarm handling for health monitoring: Operator strategies used in an electrical control room of a rail network

Alarm management is a key component of the successful operation of a prognostic or health-monitoring technology. Although alarms can alert the operator to critical information, false alarms and alarm flooding can cause major difficulties for successfully diagnosing and acting upon infrastructure faults. Human factors approaches seek to design more-effective alarm systems through a deep understanding of the contextual factors that influence alarm response, including strategies and heuristics used by operators. This paper presents an extensive analysis of alarm-handling activity in the setting of an Electrical Control Room on the rail network. The analysis is based on contextual observation, and the application of a time-stamped observation checklist. Functions, performance requirements, and general operating conditions that influence alarm handling are presented, delineating the typical operational constraints that need to be considered in the design and deployment of asset-based alarm systems. The analysis of specific alarm-handling incidents reveals the use of specific strategies that may bias operator performance. Implications for the design of health-monitoring systems are discussed.

Cognitive Work Analysis practicality and limitations in complex control systems: a case of alarm handling

Abstract Cognitive Work Analysis is an approach to understand work in complex socio-technical environments. Despite the promising advantages of framing cognitive tasks within this model most of the published research is limited to first stages of CWA and developed an abstract understanding rather than tangible design recommendations. In this paper alarm handling in rail electrical control room was chosen as the case study which conducts CWA in order to understand its potential and limitations and to determine the challenges in doing so.

Evaluating the impact of rail research: Principles to maximise innovation uptake

This paper presents an analysis of railway research carried out in the UK, coupled with interview data from those with active experience of rail research. The aim of this work is to better understand the impact of research in order to identify key factors that influence successful implementation of outcomes, or present barriers to the development and adoption of rail innovation. The paper introduces the innovation context experienced by the rail sector, comparing it with other industries leading to a discussion of research gaps. Data was collected using interviews with industry research experts combined with an analysis of a sample of case studies, dating primarily from 1988 onwards. These data were assessed against three analytical frameworks: barriers and enablers, research process and research impact. Particular emphasis is placed on how research in the rail sector does not always follow the linear process typified by Technology Readiness Levels. The results of this exercise are then discussed leading to the conclusions including the definition of mechanisms that, if followed, could lead to maximising uptake of railway research.