面向个性化自动驾驶:情感偏好风格适应框架

Jiali Ling, Jialong Li, K. Tei, Shinichi Honiden
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引用次数: 2

摘要

虽然自动驾驶有望为未来的交通铺平道路,但它经常遇到阻力。其中一个原因可能是,在撰写本文时,自动驾驶仍然无法满足人们的个性化需求。此外,驾驶自动驾驶汽车时的不熟悉和不舒服可能会让司机感到压力,并对汽车产生不信任。为此,我们提出了一个情绪偏好风格适应(EPSA)框架。该框架可以从驾驶员的脑电图信号中识别驾驶员的情绪来分析和确定驾驶员的驾驶偏好。然后,它将调整车辆的驾驶行为风格,以适应驾驶员的偏好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards Personalized Autonomous Driving: An Emotion Preference Style Adaptation Framework
Although autonomous driving is expected to pave the way for the future of transportation, it is often met with resistance. One of the reasons for this may be that, as of this writing, autonomous driving still cannot meet the individual needs of people. Furthermore, the unfamiliarity and discomfort when riding in an autonomous vehicle can cause drivers to feel stressed and distrustful of the vehicle. To this end, we propose an Emotion Preference Style Adaptation (EPSA) framework. The framework can analyze and determine a driver’s driving preferences from the emotion which is recognized from their EEG signals. And then it will adapt the style of the vehicle’s driving behavior to suit the driver’s preference.
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