Phenikaa Research and Technology Institute, Phenikaa Group, Hanoi, Vietnam.
Faculty of Vehicle and Energy Engineering, Phenikaa University, Hanoi, Vietnam.
Traffic Inj Prev. 2022;23(5):221-225. doi: 10.1080/15389588.2022.2051019. Epub 2022 Mar 25.
A driver's internal state is a critical factor influencing driving performance, especially in cases of surprise or shock in response to unexpected incidents while driving. This study was designed to investigate the brain activity of a senior driver in response to simulated unexpected vehicle motion, compared with a relaxed state and normal driving.
To accomplish this, we created a driving simulator paradigm wherein participants were involved in one of the following three scenarios: sitting down and relaxing, normal driving around the city with traffic signals and other vehicles, and the exiting of a parking area. In the scenario where the driver was to exit the parking area, the gear was switched automatically by the CarMaker software without the driver being notified, leading to an unexpected condition. The driver's internal states were classified by artificial intelligence, based on information obtained through four-channel near-infrared spectroscopy.
Significant differences were observed between the hemodynamic responses obtained in the three conditions. Ultimately, this method can be used to update advanced driver assistance systems, with a view to preventing future traffic accidents, by activating in-vehicle safety functions based on the driver's condition.
A driver's internal states in a panic situation while driving can be detected using near-infrared spectroscopy and artificial intelligence.
驾驶员的内部状态是影响驾驶性能的关键因素，尤其是在驾驶时对意外事件做出意外或震惊反应的情况下。本研究旨在调查模拟意外车辆运动时老年驾驶员的大脑活动，与放松状态和正常驾驶进行比较。
为此，我们创建了一个驾驶模拟器范例，参与者可以在以下三种情况之一中进行：坐下来放松，在城市中交通信号灯和其他车辆周围正常驾驶，以及驶出停车场。在要驶出停车场的情况下，驾驶员没有接到通知，软件自动切换档位，导致出现意外情况。驾驶员的内部状态由人工智能根据四通道近红外光谱仪获取的信息进行分类。
在三种情况下获得的血液动力学响应存在显著差异。最终，这种方法可以用于更新高级驾驶员辅助系统，通过根据驾驶员的状况激活车载安全功能，防止未来的交通事故。
可以使用近红外光谱和人工智能检测驾驶员在驾驶时恐慌情况下的内部状态。
