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基于模型的驾驶汽车时A柱造成部分视野受限的操作后果预测

Model-Based Prediction of Operation Consequences When Driving a Car to Compensate for a Partially Restricted Visual Field by A-Pillars.

作者信息

Ueda Sayako, Sato Toshihisa, Kumada Takatsune

机构信息

TOYOTA Collaboration Center, RIKEN Center for Brain Science, Wako, Japan.

Human-Centered Mobility Research Center, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan.

出版信息

Front Hum Neurosci. 2021 Nov 4;15:697295. doi: 10.3389/fnhum.2021.697295. eCollection 2021.

DOI:10.3389/fnhum.2021.697295
PMID:34803628
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8600357/
Abstract

The partial restriction of a driver's visual field by the physical structure of the car (e.g., the A-pillar) can lead to unsafe situations where steering performance is degraded. Drivers require both environmental information and visual feedback regarding operation consequences. When driving with a partially restricted visual field, and thus restricted visual feedback, drivers may predict operation consequences using a previously acquired internal model of a car. To investigate this hypothesis, we conducted a tracking and driving task in which visual information was restricted to varying degrees. In the tracking task, participants tracked a moving target on a computer screen with visible and invisible cursors. In the driving task, they drove a real car with or without the ability to see the distant parts of a visual field. Consequently, we found that the decrease in tracking performance induced by visual feedback restriction predicted the decrease in steering smoothness induced by visual field restriction, suggesting that model-based prediction was used in both tasks. These findings indicate that laboratory-based task performance can be used to identify drivers with low model-based prediction ability whose driving behavior is less optimal in restricted vision scenarios, even before they obtain a driver's license. However, further studies are required to examine the underlying neural mechanisms and to establish the generalizability of these findings to more realistic settings.

摘要

汽车的物理结构(如A柱)对驾驶员视野的部分限制可能会导致不安全情况,使转向性能下降。驾驶员既需要环境信息,也需要关于操作后果的视觉反馈。当在视野部分受限、从而视觉反馈也受限的情况下驾驶时,驾驶员可能会使用先前获得的汽车内部模型来预测操作后果。为了研究这一假设,我们进行了一项跟踪和驾驶任务,其中视觉信息受到不同程度的限制。在跟踪任务中,参与者用可见和不可见的光标在电脑屏幕上跟踪一个移动目标。在驾驶任务中,他们驾驶一辆真车,视野中能看到或看不到远处部分。结果,我们发现视觉反馈限制引起的跟踪性能下降预示着视野限制引起的转向平稳性下降,这表明在两项任务中都使用了基于模型的预测。这些发现表明,基于实验室的任务表现可用于识别那些基于模型的预测能力较低的驾驶员,这些驾驶员在视野受限的情况下驾驶行为不太理想,甚至在他们获得驾照之前就是如此。然而,还需要进一步研究来检验潜在的神经机制,并确定这些发现在更现实场景中的普遍性。

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