Abstract
Identification of driver state is a desirable element of many proposed vehicle active safety systems (e.g., collision detection and avoidance, automated highway, and road departure warning systems). In the paper, driver state assessment is considered in the context of a road departure warning and intervention system. A system identification approach, using vehicle lateral position as the input and steering wheel position as the output, is used to develop a model and to update its parameters during driving. Preliminary driving simulator results indicate that changes in the bandwidth and/or parameters of such a model may be useful indicators of driver fatigue. The approach is then applied to data from 12 2-h highway driving runs conducted in a full-vehicle driving simulator. The identified model parameters (/spl zeta/ /spl omega//sub n/, and DC gain) do not exhibit the trends expected as lane keeping performance deteriorates, despite having acceptably white residuals. As an alternative, model residuals are compared in a process monitoring approach using a model fit to an early portion of the 2-h driver run. Model residuals show the expected trends and have potential in serving as the basis for a driver state monitor.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
