Research On Several Issues In Human-Vehicle Interaction System Based On Neuroergonomics

In recent years, the automobile traffic accident rate in our country remains high. According to the report, motor vehicle driver’s subjective factor is the main cause of road accidents. Driving a car is a complex mental task. The brain’s cognition, judgment, response and coordination dominate driver’s every step of the operation and have an influence on the safty of people and vehicle. The study of the nature and rules of driver’s brain has important significance for driving safety and driving comfort.The nature and law of human’s brain belong to the category of neurology; the vehicle design problems for safety and amenity belong to the category of ergonomics. The combination of neurology and ergonomics is neuroergnomics. Neuroergnomics is the study of brain activities and human behavior at work. As an interdisciplinary study, it combines neuroscience and human factors together. Based on the human brain function analysis, the discipline aims to match the technology and products with the capabilities and limitations of brain so that people can work more efficient and safely with the equipment and products.EEG analysis methods were applied to study the human-vehicle system based on neuroergonomics theory. This paper studied the driver’s cognitive process, driver’s status under influence of alcohol, and driver’s fatigue status by collecting EEG signals, processing EEG signals and feature extraction. The driver’s behavior rules and brain activity patterns have been put forward, which provide theoretical basis and objective index for driving safty. The study was developed and researched from the following four aspects:1. The influences of vehicle’s apparent color on the driver’s behavior and brain activities have been studied. The vehicle’s apparent color is the first visual element for other vehicle drivers on the road, which is the most significant feature of vehicle’s appearance. Vehicle of different color lead to different traffic accident rate:the traffic accident rate of the black vehicle is three times of the white vehicle. The event-related potentials (ERP) were induced using the black/white/red/blue car image. The results show that when watching white cars, the amplitude of the drivers’ERP data increased more than the drivers watching the black cars significantly. The brain electrical activity mapping (BEAM) demonstrates that:(1) Brain energy induced by white cars is higher than that induced by black car.(2) The exciting part stimulated by the white cars is mainly on the occiput, whereas the inhibition part stimulated by the black cars is mainly on the top.(3) The black car could evoke more slow waves and less fast waves than other color cars. These results indicate that there are significant differences in the EEG signals between watching different color cars, which show that different colors (including color hue, lightness and purity) have different impacts on the drivers on physiological and psychological aspects. The results have guiding significance on the prevention of vehicle rear-end collision.2. The relations between the displaying of car’s interior dashboard and driver’s cognitive mechanism have been studied. Dashboard is a data platform displaying the operating condition of the machine, which is the information medium between the operator and the machine. The dashboard should enable the operator work safely and effectively. The design elements of the prompt for symbolic on the dashboard include shape, size, and weight. The influences of the prompt for symbolic size on visual working memory were studied using change detection paradigm. The experiment studied the differences of subjects’ working memory with different sizes (9cm,6cm) and different working loads (4icons,2icons). The results show that the reaction time with the small prompt for symbolic is significantly shorter than that with the big prompt for symbolic; the correct response rate and response speed of the high loads work are lower than that of the low loads work; and the high loads work evoked bigger CDA amplitude than the low loads work.3. Drivers’ behavior and cognitive abilities on the influence of alcohol were studied. The subjects were asked to take the simulated driving experiment under the case of drinking and not drinking respectively. And the classical oddball stimulating experiments was taken to study the driver’s cognitive process under the influence of alcohol. It was found that the drunk drivers’P2amplitudes in the ERP data decreased, and the behavioral response speed and response accuracy decreased. Moreover, based on the ERP data of left brain and right brain, there are more obvious damages due to the alcohol on the right brain than the left one. These results demonstrate that the alcohol play a diminished role on the brain function, and the endurance of the right brain is weaker than the left brain.4. The fatigue taxi driver’s EEG signals were studid. The taxi driver’s EEG signals, which have three states:before driving, fatigue, after rest, were collected. The EEG signals were de-noised. The wavelet entropy and chaotic correlation dimension of the EEG signals were calculated to get the feature of fatigue driving. It was found that:the wavelet entropy of H and R formula of fatigue driver’s EEG is significantly higher than the normal state EEG; the wavelet entropy of H and R formula of the driver’s EEG after rest is significantly lower than the fatigue state EEG; the chaos correlation dimension of fatigue driver’s EEG is significantly lower than the normal state EEG. The fatigue driver’s feature extraction methods were put forward, which provide theory basis to the driver’s fatigue warning system.