Analysis On The Effect Of Driving Load On The Driver’s Cerebral Autoregulation

In recent years, the number of cars has increased year by year, so the security problem has attracted much attention. Many literatures show that the driver is easy to sudden stroke and other cardiovascular diseases on the road, and the high driving load is one of the important factors. In addition, the vehicle human machine interface is becoming more and more complex in order to meet the requirements of the multi functionality of the vehicle, but it can lead to high driving load. The scientific evaluation of the vehicle human-machine interface design has become an important issue to be solved in the field of automotive engineering. The purpose of this study is to analyze the driving load from the point of human physiological mechanism, so as to provide a reliable basis for the optimization design of vehicle human machine interface.Cerebral autoregulation can reflect the brain’s ability to regulate the cerebral blood flow in the face of blood pressure changes in the body. And the brain’s oxygen consumption is bound to increase when the driver is in response to high driving load. There is a need for adequate cerebral blood perfusion in order to ensure that the brain cells can perform normal metabolic activities. Therefore, it is feasible to evaluate the driving load by studying the dynamic cerebral autoregulation. For the analysis of dynamic cerebral autoregulation, the near infrared spectroscopy has been recognized as a very suitable technology. On the one hand, it has a good time resolution (close to millisecond) and good spatial resolution (5-10 mm), so it can detect changes in the oxygen hemoglobin concentration of the brain tissue microcirculation. Then combining with the detection of arterial blood pressure, we can realize the local assessment of cerebral autoregulation in different eloquent areas. On the other hand, the oxygen hemoglobin signal detected using near infrared spectroscopy equipment is not susceptible to motion noise, and the detection equipment has a high portability, so it is convenient to carry out real-time detection for the driver.In this paper, a vigilance task platform was designed to simulate the driver’s actual driving load. Continuous recordings of oxygen hemoglobin signals were obtained from the prefrontal cortex and motor cortical areas of young healthy drivers during resting state and vigilance task state, and the arterial blood pressure was simultaneously recorded. Then, the coupling relationship between the two signals in the low frequency bands was analyzed by the coherence method based on Morlet wavelet, so as to evaluate the influence of driving load on the driver’s cerebral autoregulation. Our study found that the wavelet coherence and phase coherence are significantly different in certain frequency ranges between the resting state and vigilance task state. The results show that the driving load has a significant impact on the cerebral autoregulation.The method based on wavelet transform can show more physiological signal in time-frequency domain, which is useful for extracting the signal components of interest. The wavelet coherence and phase coherence describe the synchronization relationship in time-frequency domain between two stochastic processes, and it can provide a new perspective to evaluate the driving load by applying them to analyze the driver’s cerebral autoregulation.