Model analysis of adaptive car driving behavior

P.H. Wewerinke

doi:10.1109/ICSMC.1996.561332

Model analysis of adaptive car driving behavior

P.H. Wewerinke

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

7 Citations (Scopus)

112 Downloads (Pure)

Abstract

This paper deals with two modeling approaches to car driving. The first one is a system theoretic approach to describe adaptive human driving behavior. The second approach utilizes neural networks. As an illustrative example the overtaking task is considered and modeled in system theoretic terms. Model results are used to teach a neural network. The results show that a neural network is able to learn this task even when certain task variables change. The next step is to perform an experiment with real human operators in order to assess the validity of both modeling approaches and their relative merit

Original language	Undefined
Title of host publication	IEEE International Conference on Systems, Man and Cybernetics
Place of Publication	Beijing, China
Publisher	IEEE
Pages	2558-2563
Number of pages	6
ISBN (Print)	9780780332805
DOIs	https://doi.org/10.1109/ICSMC.1996.561332
Publication status	Published - 14 Oct 1996
Event	IEEE International Conference on Systems, Man and Cybernetics 1996 - Beijing, China, Beijing, China Duration: 14 Oct 1996 → 17 Oct 1996

Publication series

Name
Publisher	IEEE
Volume	4

Conference

Conference	IEEE International Conference on Systems, Man and Cybernetics 1996
City	Beijing, China
Period	14/10/96 → 17/10/96
Other	14-17 Oct. 1996

Keywords

IR-31135
METIS-141777

Access to Document

10.1109/ICSMC.1996.561332

00561332

Cite this

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title = "Model analysis of adaptive car driving behavior",

abstract = "This paper deals with two modeling approaches to car driving. The first one is a system theoretic approach to describe adaptive human driving behavior. The second approach utilizes neural networks. As an illustrative example the overtaking task is considered and modeled in system theoretic terms. Model results are used to teach a neural network. The results show that a neural network is able to learn this task even when certain task variables change. The next step is to perform an experiment with real human operators in order to assess the validity of both modeling approaches and their relative merit",

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AB - This paper deals with two modeling approaches to car driving. The first one is a system theoretic approach to describe adaptive human driving behavior. The second approach utilizes neural networks. As an illustrative example the overtaking task is considered and modeled in system theoretic terms. Model results are used to teach a neural network. The results show that a neural network is able to learn this task even when certain task variables change. The next step is to perform an experiment with real human operators in order to assess the validity of both modeling approaches and their relative merit

KW - IR-31135

KW - METIS-141777

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DO - 10.1109/ICSMC.1996.561332

M3 - Conference contribution

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