Applying ergonomics within the multi-modelling paradigm with an example from multiple UAV control

Golightly, David; Gamble, Carl; Palacín, Roberto; Pierce, Ken

doi:10.1080/00140139.2020.1723683

Cited by 10 publications

(6 citation statements)

References 64 publications

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“…This represents an explicit study of how interactions shape work in dynamic, complex, and adaptive systems, a useful contribution to the literature to deepen our understanding of interactions. Our use of network analysis represents an additional analytic method to understand interactions in sociotechnical systems, in addition to computational modeling methods previously identified and applied, including simulation, system dynamics modeling, agent-based simulation, and hybrid approaches (e.g., Davis et al, 2020; Golightly et al, 2020; Gorman et al, 2019; Guastello, 2017; Hettinger et al, 2015; Holman et al, 2020). ENA, while developed in the learning science community, has proven useful in HFE research (Wooldridge et al, 2018; Wooldridge & Haefli, 2019).…”

Section: Discussionmentioning

confidence: 99%

Interactions in Sociotechnical Systems: Achieving Balance in the Use of an Augmented Reality Mobile Application

Wooldridge

Morgan²,

Ramadhani

et al. 2022

Hum Factors

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Objective We explore relationships between barriers and facilitators experienced by users to understand dynamic interactions in sociotechnical systems and improve a mobile phone-based augmented reality application that teaches users about the contents of a standardized pediatric code cart. Background Understanding interactions between performance obstacles and facilitators can provide guidance to (re)designing sociotechnical systems to improve system outcomes. Clinicians should know about contents and organization of code carts, and an augmented reality mobile application may improve that knowledge but changes the sociotechnical system in which they learn. Prior work identified barriers and facilitators impacting the use of this application—participants described dimensions together, indicating interactions that are explored in the current study. Method We conducted four focus groups (number of clinicians = 18) and two interviews with clinicians who used the application. We performed a secondary analysis of focus group data exploring interactions between previously identified barriers and facilitators to application use. We used epistemic network analysis to visualize these interactions. Results Work system barriers interacted with barriers and facilitators interacted with facilitators to amplify cumulative negative or positive impact, respectively. Facilitators balanced barriers, mitigating negative impact. Facilitators also exacerbated barriers, worsening negative impact. Conclusion Barriers and facilitators interact and can amplify, balance, and exacerbate each other—notably, positives are not always positive. To obtain desired outcomes, interactions must be further considered in sociotechnical system design, for example, the potential improvements to the application we identified.

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Section: Discussionmentioning

confidence: 99%

Interactions in Sociotechnical Systems: Achieving Balance in the Use of an Augmented Reality Mobile Application

Wooldridge

Morgan²,

Ramadhani

et al. 2022

Hum Factors

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“…Several researchers have simulated human behavior in order to study the system-level performance of human-robot teams. Using multimodeling, Golightly et al 27 give an example of an operator-UAV team, where the operator's task sequence and the UAV's flight in windy conditions are modeled. In this way, surprising interactions were uncovered, such as windy conditions' decreasing wait time in some instances (due to serendipitous delays leading to more consistent operator workload).…”

Section: Simulated Human Behavior In Human-agent Teamsmentioning

confidence: 99%

“…Several researchers have simulated human behavior in order to study the system‐level performance of human‐robot teams. Using multi‐modeling, Golightly et al 27 . give an example of an operator‐UAV team, where the operator's task sequence and the UAV's flight in windy conditions are modeled.…”

Section: Related Workmentioning

confidence: 99%

Modeling, simulation, and trade‐off analysis for multirobot, multioperator surveillance

Humann

Fletcher

Gerdes

2023

Systems Engineering

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As unmanned vehicles become smaller and more autonomous, it is becoming feasible to use them in large groups with comparatively few human operators. Design and analysis of such distributed systems are complicated by the many interactions among agents and phenomena of human behavior. In particular, human susceptibility to fatigue and cognitive overload can introduce errors and uncertainty into the system. In this paper, we demonstrate how advanced computational tools can help to overcome these engineering difficulties by optimizing multirobot, multioperator surveillance systems for cost, speed, accuracy, and stealth according to diverse user preferences in multiple case studies. The tool developed is a graphical user interface that returns the optimal number and mix of diverse agent types as a function of the user's trade‐off preferences. System performance prediction relies on a multiagent simulation with submodels for human operators, fixed‐wing unmanned aerial vehicles (UAVs), quadrotor UAVs, and flapping wing UAVs combined in different numbers.

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“…In some cases, it may be possible to include multiple instances of a model (e.g. to have multiple FMUs of multiple UAVs flying at the same time 48 ) In this way, it is possible to conduct rapid Design Space Exploration (DSE) of a given systems problem.…”

Section: Adoption and Impactmentioning

confidence: 99%

“…47 applied the approach to combine models of both the cyber and physical aspects of an emission reduction system for a two-stroke engine. 48 use multi-modelling to study human performance implications in multiple UAV control by modelling the impact of different operator responses under variable workload conditions. Multi-modelling has also been successfully used to support digital twinning.…”

Section: Introductionmentioning

confidence: 99%

A feasibility assessment of multi-modelling approaches for rail decarbonisation systems simulation

Golightly

Pierce

Palacín

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part F:

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Simulation is an important tool to support rail decarbonisation but can be challenging due to heterogeneous models, simulation tools and skill sets, and concerns around intellectual property. Multi-modelling, a proven methodology in sectors such as aerospace and automotive, uses Functional Mock-up Interface (FMI) and co-simulation to potentially overcome these problems. This paper presents a feasibility study of multi-modelling for rail decarbonisation, using a combination of audit of current state of the art, technical implementation and stakeholder consultation. The audit showed that while current uptake of FMI in rail is low, there is potential to repurpose models from pre-existing tools and apply them within multi-modelling. The technical feasibility assessment demonstrated how multi-modelling could generate flexible simulation outputs to identify decarbonisation systems effects both for urban and mainline rail, including rapid integration of pre-existing MATLAB Simulink models. Work with industry stakeholders identified use cases where multi-modelling would benefit rail decarbonisation, as well as barriers and enablers to adoption. Overall, the study demonstrates the feasibility and considerations for multi-modelling to support rail decarbonisation efforts, and the future developments necessary for wider rollout.

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Applying ergonomics within the multi-modelling paradigm with an example from multiple UAV control

Cited by 10 publications

References 64 publications

Interactions in Sociotechnical Systems: Achieving Balance in the Use of an Augmented Reality Mobile Application

Interactions in Sociotechnical Systems: Achieving Balance in the Use of an Augmented Reality Mobile Application

Modeling, simulation, and trade‐off analysis for multirobot, multioperator surveillance

A feasibility assessment of multi-modelling approaches for rail decarbonisation systems simulation

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