Cognitive workload analysis in rail signalling environments

Krehl, Claudia; Balfe, Nora

doi:10.1007/s10111-013-0266-7

Cited by 11 publications

(6 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This method provides good prediction of workload profile but requires a lot of time dedicated for the task analysis, and provides a granularity for the results which are sometimes not required. Balfe [1] also confirmed this point on view after applying a similar method called Multiple Resource Questionnaire in a signaling study.…”

Section: Current Workload Methods and Toolsmentioning

confidence: 64%

“…Signaling activities include monitoring, regulating, verbal communication, operating infrastructure, using paper timetable, and processing documentation (paperwork) [1]. The goals of workload studies are diverse including the definition of an acceptable level of workload for a workstation, contribution of workload into an accident, work organization and break times, definition of workstation boundaries, evaluation of the impact of additional/change of infrastructure, the impact of a timetable change, ARS inclusion (Automatic Route Setting), and the use of alternative technologies (i.e.…”

Section: B Scope and Terminologymentioning

confidence: 99%

See 1 more Smart Citation

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)

View full text Add to dashboard Cite

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.

show abstract

Section: Current Workload Methods and Toolsmentioning

confidence: 64%

Section: B Scope and Terminologymentioning

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)

View full text Add to dashboard Cite

show abstract

“…Indeed, there are many factors, both physical and cognitive, that affect the users' performance and the quality of manufacturing processes: from physical workload, due to uncomfortable postures, to task complexity, overload of information, or time pressure Biondi et al 2020;Young et al 2015). Cognitive workload analysis is more frequently used in complex human-interaction systems in which human errors have a crucial importance, such as railways and aerospace fields (Krehl and Balfe 2014;Alaimo et al 2020). Workload can be defined in terms of experienced load; it is not only task-specific, but also person-specific (Rouse, Edwards, and Hammer 1993).…”

Section: Research Backgroundmentioning

confidence: 99%

Creation of a UX index to design human tasks and workstations

Grandi

Peruzzini

Cavallaro

et al. 2021

International Journal of Computer Integrated Manufacturing

View full text Add to dashboard Cite

Successful interaction with complex processes, like those in the modern factory, is based on the system's ability to satisfy the user needs during human tasks, mainly related to performances, physical comfort, usability, accessibility, visibility, and mental workload. However, the 'real' user perception is hidden and usually difficult to detect. User eXperience (UX) is a useful concept related to subjective perceptions and responses that result from the interaction with a product, system or process, including users' emotions, beliefs, preferences, perceptions, physical and psychological responses, behaviors and accomplishments that occur before, during and after use. The paper proposes the creation of a User eXperience Index (UXI) to assess the quality of human-system interaction during job tasks and, consequently, evaluate both process and workstation. The proposed approach has been applied to improve the design of assembly human tasks, using a virtual simulated case study focusing on tractor assembly. Tests with users, with different levels of expertise, allowed us to validate the proposed approach and to optimize the assembly task sequence. Results showed how the proposed UXI can validly objectify the workers' experience and can be validly used to improve the design of human tasks.

show abstract

“…However, these are mostly focused on physical (and in particular musculoskeletal) workload and generally adopt the definition of participatory to incorporate and involve endusers within the organization during the design and implementation of the workload evaluations. Similarly, much work has been done in cognitive workload assessment, in a range of applications areas, such as driving (Reimer & Mehler, 2011;Zhang et al, 2004), air traffic control (Ayaz et al, 2010;Marchitto et al, 2016) and rail (Krehl & Balfe, 2014;Pickup et al, 2005) but not within automotive manufacturing. The present paper explores the process adopted to develop/propose a participatory workload assessment program within automotive manufacturing.…”

mentioning

confidence: 99%

Cognitive and metabolic workload assessment techniques: A review in automotive manufacturing context

Dadashi

Lawson

Marshall

et al. 2021

Hum Ftrs & Erg Mfg Svc

View full text Add to dashboard Cite

Ergonomics assessment in the automotive industry has, to date, focused mainly on physical ergonomics, for example, manual handling and posture. However, workload and, in particular, metabolic and cognitive workload, contributes to worker efficiency but has not received sufficient attention to yield practical guidance for industry. Successful workload assessment requires in-depth understanding of the context in which it will be conducted and of the various assessment techniques which will be applied, with consideration given to factors such as feasibility, resources, and skill of the assessor. These requirements are met with challenges within large and complex organizations and are often dealt with in a piecemeal and isolated matter (i.e., reactive workload assessment). The present paper explores these challenges within the automotive manufacturing industry and aims to develop a decision matrix to guide effective selection of workload assessment techniques focused on metabolic and cognitive demands. It also presents the requirements for time, equipment, and knowledge to implement these techniques as part of a participatory ergonomics approach. Early findings suggest that most assessment techniques reviewed require further development, for example, to establish the acceptance criteria for the specific workload scenario. However, five methods (Garg, Borg RPE, IPAQ, SWAT, and NASA-TLX) are ready to use in certain applications.Ultimately, the findings suggest that it is possible to implement a participatory workload evaluation program within large and complex manufacturing plants.

show abstract

Cognitive workload analysis in rail signalling environments

Cited by 11 publications

References 17 publications

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

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

Creation of a UX index to design human tasks and workstations

Cognitive and metabolic workload assessment techniques: A review in automotive manufacturing context

Contact Info

Product

Resources

About