Sensorimotor adaptation when steering with altered vehicle dynamics
Autor: | Kristen L. Macuga |
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Rok vydání: | 2018 |
Předmět: |
business.product_category
Computer science 05 social sciences Transportation Context (language use) 050105 experimental psychology Vehicle dynamics 03 medical and health sciences 0302 clinical medicine Control theory Automotive Engineering Electric vehicle 0501 psychology and cognitive sciences business Adaptation (computer science) ComputingMilieux_MISCELLANEOUS 030217 neurology & neurosurgery Applied Psychology Civil and Structural Engineering |
Zdroj: | Transportation Research Part F: Traffic Psychology and Behaviour. 59:115-123 |
ISSN: | 1369-8478 |
DOI: | 10.1016/j.trf.2018.08.018 |
Popis: | Though adaptive sensorimotor processes have been studied for simple, laboratory tasks such as reaching, less is known about how they might function during complex, real-world behaviors such as steering. The effects of altered vehicle dynamics on steering were investigated, using a physically moving electric vehicle outfitted with a portable virtual reality system. Vehicle dynamics were manipulated via changes in steering gain. Three groups of participants attempted to steer a series of curving paths with a lower steering gain, a higher steering gain, or a reversed steering gain. This adaptation phase was compared with pre-adaptation and post-adaptation phases, for which the steering gain was unaltered. As drivers accrued experience with the altered steering gains, they became more accurate and fluent in steering a vehicle. Adaptation to subtler steering gain changes was rapid, and without aftereffects, but adaptation to a more extreme steering gain (i.e., reversed) was slower, with aftereffects upon the initial return to the unaltered gain in the post-adaptation phase. Drivers can adapt relatively quickly to changes in steering gain, incorporating the relevant dynamics of the vehicle. The approach developed here could be used to refine theories of sensorimotor adaptation in the context of more practical applications, such as real-world human-tool systems. |
Databáze: | OpenAIRE |
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