CLC number: TP391; U463.6
On-line Access: 2012-03-01
Received: 2011-07-17
Revision Accepted: 2011-12-07
Crosschecked: 2012-02-09
Cited: 8
Clicked: 8460
Lei He, Chang-fu Zong, Chang Wang. Driving intention recognition and behaviour prediction based on a double-layer hidden Markov model[J]. Journal of Zhejiang University Science C, 2012, 13(3): 208-217.
@article{title="Driving intention recognition and behaviour prediction based on a double-layer hidden Markov model",
author="Lei He, Chang-fu Zong, Chang Wang",
journal="Journal of Zhejiang University Science C",
volume="13",
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pages="208-217",
year="2012",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.C11a0195"
}
%0 Journal Article
%T Driving intention recognition and behaviour prediction based on a double-layer hidden Markov model
%A Lei He
%A Chang-fu Zong
%A Chang Wang
%J Journal of Zhejiang University SCIENCE C
%V 13
%N 3
%P 208-217
%@ 1869-1951
%D 2012
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.C11a0195
TY - JOUR
T1 - Driving intention recognition and behaviour prediction based on a double-layer hidden Markov model
A1 - Lei He
A1 - Chang-fu Zong
A1 - Chang Wang
J0 - Journal of Zhejiang University Science C
VL - 13
IS - 3
SP - 208
EP - 217
%@ 1869-1951
Y1 - 2012
PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.C11a0195
Abstract: We propose a model structure with a double-layer hidden Markov model (HMM) to recognise driving intention and predict driving behaviour. The upper-layer multi-dimensional discrete HMM (MDHMM) in the double-layer HMM represents driving intention in a combined working case, constructed according to the driving behaviours in certain single working cases in the lower-layer multi-dimensional Gaussian HMM (MGHMM). The driving behaviours are recognised by manoeuvring the signals of the driver and vehicle state information, and the recognised results are sent to the upper-layer HMM to recognise driving intentions. Also, driving behaviours in the near future are predicted using the likelihood-maximum method. A real-time driving simulator test on the combined working cases showed that the double-layer HMM can recognise driving intention and predict driving behaviour accurately and efficiently. As a result, the model provides the basis for pre-warning and intervention of danger and improving comfort performance.
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Open peer comments: Debate/Discuss/Question/Opinion
<1>
Teng Fei@Beijing Institute of tech<19283746_2008@sohu.com>
2014-03-31 16:20:25
I wonna know more about Markov model