Abstract
For establishing a standard of design element of the smart highway, this study investigated driver's anxiety EEG according to running speeds and geometric designs. Also, the experiment was implemented on 60 subjects. Based on running speed data and brainwave data, which were obtained from the experiment, this study analyzes anxiety EEG according to running speeds and geometric designs, and finally draws a forecasting model of anxiety EEG by selecting affecting factors of anxiety EEG. Forecasting model shows that left curve is the most influential on anxiety EEG figure. The reason is because when driver is driving on the first-lane, his or her visibility is impeded by a median strip. For this reason, anxiety EEG figure increases. And also steep downward slope and large radius of curve are heavily influential on driver's anxiety EEG figure. It is judged that anxiety EEG figure is increased by high speed on those section. Thus, the forecasting model of anxiety EEG suggested on this study will be utilized for design phase, and will decide the design speed on the superhighway. So, it will be used to make practical and safety road.
