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Study on driver’s braking intention identification based on functional near-infrared spectroscopy

机译:基于功能近红外光谱的驾驶员制动意向研究

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摘要

Purpose - Cooperative driving refers to a notion that intelligent system sharing controlling with human driver and completing driving task together. One of the key technologies is that the intelligent system can identify the driver’s driving intention in real time to implement consistent driving decisions. The purpose of this study is to establish a driver intention prediction model. Design/methodology/approach - The authors used the NIRx device to measure the cerebral cortex activities for identifying the driver’s braking intention. The experiment was carried out in a virtual reality environment. During the experiment, the driving simulator recorded the driving data and the functional near-infrared spectroscopy (fNIRS) device recorded the changes in hemoglobin concentration in the cerebral cortex. After the experiment, the driver’s braking intention identification model was established through the principal component analysis and back propagation neural network. Findings - The research results showed that the accuracy of the model established in this paper was 80.39 per cent. And, the model could identify the driver’s braking intent prior to his braking operation. Research limitations/implications - The limitation of this study was that the experimental environment was ideal and did not consider the surrounding traffic. At the same time, other actions of the driver were not taken into account when establishing the braking intention recognition model. Besides, the verification results obtained in this paper could only reflect the results of a few drivers’ identification of braking intention. Practical implications - This study can be used as a reference for future research on driving intention through fNIRS, and it also has a positive effect on the research of brain-controlled driving. At the same time, it has developed new frontiers for intention recognition of cooperative driving. Social implications - This study explores new directions for future brain-controlled driving and wheelchairs. Originality/value - The driver’s driving intention was predicted through the fNIRS device for the first time.
机译:目的 - 合作驾驶是指智能系统共享控制人员和完成驾驶任务的概念。其中一个关键技术是智能系统可以实时识别驾驶员的驾驶意图,实现一致的驾驶决策。本研究的目的是建立驾驶员意图预测模型。设计/方法/方法 - 作者使用NIRX设备来测量用于识别驾驶员制动意图的大脑皮质活动。实验是在虚拟现实环境中进行的。在实验期间,驾驶模拟器记录了驱动数据和功能近红外光谱(FNIR)器件记录了大脑皮层中血红蛋白浓度的变化。实验结束后,通过主成分分析和反向传播神经网络建立驾驶员制动意图识别模型。结果 - 研究结果表明,本文建立的模型的准确性为80.39%。而且,该模型可以在制动操作之前识别驾驶员的制动意图。研究限制/影响 - 本研究的局限性是实验环境是理想的,并没有考虑周围的交通。同时,在建立制动意图识别模型时,不会考虑驱动程序的其他行动。此外,本文获得的验证结果只能反映一些司机识别制动意图的结果。实际意义 - 本研究可作为通过FNIR驾驶意图的未来研究的参考,对脑控制驾驶的研究也具有积极影响。与此同时,它开发了新的前沿,以确认合作驾驶。社会影响 - 本研究探讨了未来脑控制驾驶和轮椅的新方向。原创性/值 - 首次通过FNIRS设备预测驾驶员的驾驶意图。

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