The Operational Demand Evaluation Checklist (ODEC) of workload for railway signalling

Pickup, Laura; Wilson, John R.; Lowe, Emma

doi:10.1016/j.apergo.2009.09.003

Cited by 17 publications

(6 citation statements)

References 21 publications

(22 reference statements)

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“…Complexity of workstations was measured using Operational Demand Evaluation Checklist (ODEC) scores and verified by subject matter experts. The ODEC tool was developed to measure the demand placed upon the signaler due to the infrastructure on a particular workstation ( Pickup, Wilson, & Lowe, 2010 ). The tool measures quantifiable aspects of the workstation such as number of signals, number of level crossings, and speeds of trains and then ranks each entity as high, medium, or low.…”

Section: Methodsmentioning

confidence: 99%

Understanding Is Key: An Analysis of Factors Pertaining to Trust in a Real-World Automation System

Balfe

Sharples²,

Wilson

2018

Hum Factors

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Objective:This paper aims to explore the role of factors pertaining to trust in real-world automation systems through the application of observational methods in a case study from the railway sector.Background:Trust in automation is widely acknowledged as an important mediator of automation use, but the majority of the research on automation trust is based on laboratory work. In contrast, this work explored trust in a real-world setting.Method:Experienced rail operators in four signaling centers were observed for 90 min, and their activities were coded into five mutually exclusive categories. Their observed activities were analyzed in relation to their reported trust levels, collected via a questionnaire.Results:The results showed clear differences in activity, even when circumstances on the workstations were very similar, and significant differences in some trust dimensions were found between groups exhibiting different levels of intervention and time not involved with signaling.Conclusion:Although the empirical, lab-based studies in the literature have consistently found that reliability and competence of the automation are the most important aspects of trust development, understanding of the automation emerged as the strongest dimension in this study. The implications are that development and maintenance of trust in real-world, safety-critical automation systems may be distinct from artificial laboratory automation.Application:The findings have important implications for emerging automation concepts in diverse industries including highly automated vehicles and Internet of things.

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Section: Methodsmentioning

confidence: 99%

Understanding Is Key: An Analysis of Factors Pertaining to Trust in a Real-World Automation System

Balfe

Sharples²,

Wilson

2018

Hum Factors

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“…Those factors are easily quantified could lend themselves to a future tool for predictive assessment of demands on ESs, this would be broadly similar to the approach taken in the ODEC (Operator Demand Evaluation Checklist) tool that is already used in assessing signaller workload in the UK (Pickup et al, 2010).…”

Section: Discussionmentioning

confidence: 99%

Span of control in supervision of rail track work

et al. 2016

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The supervision of engineering work on the railways has received relatively little examination despite being both safety-critical in its own right and having wider implications for the successful running of the railways. The present paper is concerned with understanding the factors that make different engineering works perceived as easier or harder to manage. We describe an approach building on notions of 'span of control', through which we developed the TOECAP inventory (Team, Organisation, Environment, Communication, Activity and Personal). This tool was validated through both interviews and questionnaires. As well as identifying the physical factors involved, the work also emphasised the importance of collaborative and attitudinal factors. We conclude by discussing limitations of the present work and future directions for development.

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“…ODEC [10] is a tool designed as a checklist listing quantified infrastructure factors, timetable, and events that can occur in the operated workstation. The output values provide visibility on demand parameters.…”

Section: Current Workload Methods and Toolsmentioning

confidence: 99%

D-MOD Dynamic Modelling of Operator Demand: A new simulator module for the evaluation of signaler's demand

Delamare

Lumby

Treble

et al. 2016

2016 IEEE International Conference on Intelligent Rail Transportation (ICIRT)

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Abstract-Estimating signaler demand is critical for ensuring signaling workstations are both feasible to run, and acceptable to staff. While human factors tools exist, they are typically manual, time consuming and rely of the skill of an expert. One solution, explored in this paper, is to use signaling simulators to assist in the estimation of demand.Full fidelity signaling simulators are already widely used in the UK. Simulators give the ability to ensure a consistent standard of competency ranging from normal routine tasks to abnormal situations (e.g. faults and failures) monitored by an experienced trainer/assessor. Whilst the original aim of full fidelity simulators was to support training and assessment of signalers, the requirement for an accurate timetable and infrastructure model, and of a realistic workstation Human Machine Interface (HMI), opens up other applications.The aim of the Dynamic Modelling of Operator Demand (D-MOD) project is to use the Hitachi Information Control System's simulation environment (TREsim signaling simulator) to deliver a workstation evaluation tool. The paper will present how the existing elements of simulator have been expanded and utilized for demand modelling, covering the architecture of D-MOD, the process of selecting and developing demand metrics, and the design of an HMI to deliver a working proof of concept.

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The Operational Demand Evaluation Checklist (ODEC) of workload for railway signalling

Cited by 17 publications

References 21 publications

Understanding Is Key: An Analysis of Factors Pertaining to Trust in a Real-World Automation System

Understanding Is Key: An Analysis of Factors Pertaining to Trust in a Real-World Automation System

Span of control in supervision of rail track work

D-MOD Dynamic Modelling of Operator Demand: A new simulator module for the evaluation of signaler's demand

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