Research on Complexity of Traffic Factors Based on EEG Data

Scientifically measuring the complexity of traffic factors and accurately assessing the driver's mental load can help reduce driving risks and road accidents. In order to describe the complexity of traffic factors objectively and quantitatively, the comparison experiment of traffic factors with different complexity are carried out as the research basis. In this paper, the driver's electroencephalogram (EEC) signals obtained from the experiment are analyzed, and a complexity quantization method for traffic factors based on the difference between the predicted value and the actual value of the a wave power spectral density in the parietal lobe of EEC is determined. Finally, based on the quantitative method, the complexity of pedestrian crossing, vehicle speed changing and vehicle lane changing are compared objectively and quantitatively in this paper.