Markkula, GM orcid.org/0000-0003-0244-1582, Romano, R orcid.org/0000-0002-2132-4077, Jamson, AH et al. (3 more authors) (2018) Using Driver Control Models to Understand and Evaluate Behavioral Validity of Driving Simulators. IEEE Transactions on Human-Machine Systems, 48 (6). pp. 592-603. ISSN 2168-2291
Abstract
For a driving simulator to be a valid tool for research, vehicle development, or driver training, it is crucial that it elicits similar driver behavior as the corresponding real vehicle. To assess such behavioral validity, the use of quantitative driver models has been suggested but not previously reported. Here, a task-general conceptual driver model is proposed, along with a taxonomy defining levels of behavioral validity. Based on these theoretical concepts, it is argued that driver models without explicit representations of sensory or neuromuscular dynamics should be sufficient for a model-based assessment of driving simulators in most contexts. As a task-specific example, two parsimonious driver steering models of this nature are developed and tested on a dataset of real and simulated driving in near-limit, low-friction circumstances, indicating a clear preference of one model over the other. By means of closed-loop simulations, it is demonstrated that the parameters of this preferred model can generally be accurately estimated from unperturbed driver steering data, using a simple, open-loop fitting method, as long as the vehicle positioning data are reliable. Some recurring patterns between the two studied tasks are noted in how the model’s parameters, fitted to human steering, are affected by the presence or absence of steering torques and motion cues in the simulator.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | This work is licensed under a Creative Commons Attribution 3.0 License. For more information, see http://creativecommons.org/licenses/by/3.0/ |
Keywords: | simulator validation; human performance modelling |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds) > ITS: Safety and Technology (Leeds) |
Funding Information: | Funder Grant number EPSRC EP/K014145/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 06 Jun 2018 10:36 |
Last Modified: | 13 Dec 2018 21:28 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/THMS.2018.2848998 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:131528 |