Driving Behavior Based on Big Data Analysis and EEG Data Analysis

Abstract

Abstract In recent years, as the number of automobiles in my country has increased year by year, the number of automobile accidents and casualties and the direct economic losses caused by them are very high. How to improve the level of road safety has become an important research content in the field of transportation. Driving a car is a complex activity involving perception, judgment, decision-making and manipulation, and requires the brain to coordinate and guide the driver’s driving functions. EEG signals can reflect the driver’s psychophysiological state, and then represent the driver’s perception activities. The application of EEG data analysis in driving behavior research explains the mechanism of driving behavior from a new perspective of cognitive neuroscience and brings new solutions to traffic safety problems. Driving behavior research is the main research content in the field of road safety. Recognizing and predicting the state of driving behavior is very important for the development of intelligent driving assistance systems and the improvement of road safety. This paper analyzes the EEG data while driving based on big data analysis. Firstly, the literature research method is used to summarize the EEG data analysis process and the research significance, and then the driver’s EEG data is analyzed and researched through simulated driving experiments. The relationship between its parameters and driving behavior. Experimental results show that the front area and buffer area have a strong correlation with all variables of driving behavior, especially the correlation with acceleration and forward time is about 35%. In addition, compared with other driving behavior variables, time zone has the strongest correlation with speed, about 56%. Approximately 46% of the samples are beta waves that are significantly related to driving behavior. In addition, alpha waves account for about 20% of the total number of samples, while the correlation between delta waves and driving behavior is the weakest, accounting for only about 10% of the total number of samples.