Modeling of drivers' longitudinal behavior

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceeding


In the last few years, many vehicle manufacturers have introduced advance driver support in some of their automobiles. One of those new features is adaptive cruise control (ACC), which extends the conventional cruise control system to control of relative speed and distance to other vehicles. In order to design an ACC controller, it is suitable to have a model of drivers' behavior. Our approach to find dynamical models of the drivers' behavior was to use system identification. Basic data analysis is made by means of system identification methodology, and several models of drivers' longitudinal behavior are proposed, including both linear regression models and subspace-based models. In various situations, detection for when a driver's behavior changes or deviates from the normal is useful. To that purpose, a GARCH (generalized autoregressive conditional heteroskedasticity) model was used to model the driver in situations such as arousal.


Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Control Engineering
Original languageEnglish
Title of host publicationNonlinear and Hybrid Systems in Automotive Control
Publication statusPublished - 2001
Publication categoryResearch
Event2001 IEEE/ASME International Conference on Advanced Intelligent Mechatronics - Como, Italy
Duration: 2001 Jul 8 → …


Conference2001 IEEE/ASME International Conference on Advanced Intelligent Mechatronics
Period2001/07/08 → …

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