A Research on Analytical Method of Driver-Vehicle-Environment System for Construction of Intelligent Driver Support System

In this study, a driver model with the multiple regression and the neural network is constructed to analyze the relationship between the driver's control action and the information that includes data of vehicle behavior and environment. Using these models, effectiveness of the information to control the action of a driver is examined. To evaluate the intelligent driver support systems, Mental Work Load (MWL) model is constructed with the multiple regression and the neural network. MWL is expressed as Heart Rate Variability (HRV). Measured HRV data and calculated HRV data with MWL model show good agreement. Effectiveness of information is examined using the MWL model. From these results, it is shown that the analytical method with the driver's MWL can be used to assess and improve the intelligent driver support systems as the next stage of this research.     

强风下有帆商船航行性能的研究(英文)

Ships which have large structures above water surface, such as pure car carriers (PCCs) and container vessels, have large speed reduction by wind pressure. In the present study, the running speed of a large PCC with two or more sails for using wind power is simulated. The simulated results demonstrate that the ship can keep a constant service speed even in winds of 20m/s except head and bow winds. This sail system can shorten annual average navigation time by about 4 hours per voyage.