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Modeling of drivers' longitudinal behavior

Bengtsson, Johan LU ; Johansson, Rolf LU and Sjögren, Agneta (2001) 2001 IEEE/ASME International Conference on Advanced Intelligent Mechatronics In Nonlinear and Hybrid Systems in Automotive Control p.41-58
Abstract
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... (More)
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. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
in
Nonlinear and Hybrid Systems in Automotive Control
pages
41 - 58
publisher
Springer
conference name
2001 IEEE/ASME International Conference on Advanced Intelligent Mechatronics
external identifiers
  • WOS:000179875900003
  • Scopus:0034858377
DOI
10.1109/AIM.2001.936845
language
English
LU publication?
yes
id
ce6e3280-950e-4670-9a7b-438d518d0ecc (old id 1406939)
date added to LUP
2009-06-03 15:21:49
date last changed
2017-01-01 08:04:56
@inproceedings{ce6e3280-950e-4670-9a7b-438d518d0ecc,
  abstract     = {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.},
  author       = {Bengtsson, Johan and Johansson, Rolf and Sjögren, Agneta},
  booktitle    = {Nonlinear and Hybrid Systems in Automotive Control},
  language     = {eng},
  pages        = {41--58},
  publisher    = {Springer},
  title        = {Modeling of drivers' longitudinal behavior},
  url          = {http://dx.doi.org/10.1109/AIM.2001.936845},
  year         = {2001},
}