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

• Published in: Vehicle system dynamics Vol. 37; no. 5; pp. 339 - 358
• Main Authors: Kuriyagawa, Yukiyo, Im, Hyung-Eun, Kageyama, Ichiro, Onishi, Shintaro
• Format: Journal Article
• Language: English
• Published: Colchester Taylor & Francis Group 01-05-2002; Taylor & Francis
• Subjects: Algorithms; Applied sciences; Electric, optical and optoelectronic circuits; Electronics; Exact sciences and technology; Fundamental areas of phenomenology (including applications); Intelligent control; Man machine systems; Mathematical models; Neural networks; Physics; Regression analysis; Robotics; Solid dynamics (ballistics, collision, multibody system, stabilization...); Solid mechanics; Transportation personnel; System evaluation; Vehicle driving; Model study; Regression analysis; Neural network; Information control; Modeling; Construction system; Varying speed; Mental model; Workload; Vehicle driver; Heart rate; Analytical method; System load; Intelligent system
• ISSN: 0042-3114; 1744-5159
• DOI: 10.1076/vesd.37.5.339.3525

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.